cpoerschke commented on a change in pull request #189:
URL: https://github.com/apache/solr/pull/189#discussion_r657317494
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java
##########
@@ -50,50 +49,52 @@
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
-/**
- * The ranking query that is run, reranking results using the
- * LTRScoringModel algorithm
- */
+/** The ranking query that is run, reranking results using the LTRScoringModel
algorithm */
public class LTRScoringQuery extends Query implements Accountable {
private static final Logger log =
LoggerFactory.getLogger(MethodHandles.lookup().lookupClass());
- private static final long BASE_RAM_BYTES =
RamUsageEstimator.shallowSizeOfInstance(LTRScoringQuery.class);
+ private static final long BASE_RAM_BYTES =
+ RamUsageEstimator.shallowSizeOfInstance(LTRScoringQuery.class);
// contains a description of the model
- final private LTRScoringModel ltrScoringModel;
- final private boolean extractAllFeatures;
- final private LTRThreadModule ltrThreadMgr;
- final private Semaphore querySemaphore; // limits the number of threads per
query, so that multiple requests can be serviced simultaneously
+ private final LTRScoringModel ltrScoringModel;
+ private final boolean extractAllFeatures;
+ private final LTRThreadModule ltrThreadMgr;
+ private final Semaphore
+ querySemaphore; // limits the number of threads per query, so that
multiple requests can be
Review comment:
perhaps moving the comment to a separate line would be clearer here.
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java
##########
@@ -460,23 +476,24 @@ public Explanation explain(LeafReaderContext context, int
doc)
final float finalScore = bs.score();
return ltrScoringModel.explain(context, doc, finalScore,
featureExplanations);
-
}
protected void reset() {
- for (int i = 0; i < extractedFeatureWeights.length;++i){
+ for (int i = 0; i < extractedFeatureWeights.length; ++i) {
int featId = extractedFeatureWeights[i].getIndex();
float value = extractedFeatureWeights[i].getDefaultValue();
- featuresInfo[featId].setValue(value); // need to set default value
everytime as the default value is used in 'dense' mode even if used=false
+ featuresInfo[featId].setValue(
+ value); // need to set default value everytime as the default
value is used in 'dense'
+ // mode even if used=false
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/response/transform/LTRFeatureLoggerTransformerFactory.java
##########
@@ -210,99 +209,120 @@ public void setContext(ResultContext context) {
searcher = context.getSearcher();
if (searcher == null) {
- throw new SolrException(
- SolrException.ErrorCode.BAD_REQUEST,
- "searcher is null");
+ throw new SolrException(SolrException.ErrorCode.BAD_REQUEST, "searcher
is null");
}
leafContexts = searcher.getTopReaderContext().leaves();
if (threadManager != null) {
-
threadManager.setExecutor(context.getRequest().getCore().getCoreContainer().getUpdateShardHandler().getUpdateExecutor());
+ threadManager.setExecutor(
+ context
+ .getRequest()
+ .getCore()
+ .getCoreContainer()
+ .getUpdateShardHandler()
+ .getUpdateExecutor());
}
rerankingQueriesFromContext =
SolrQueryRequestContextUtils.getScoringQueries(req);
- docsWereNotReranked = (rerankingQueriesFromContext == null ||
rerankingQueriesFromContext.length == 0);
+ docsWereNotReranked =
+ (rerankingQueriesFromContext == null ||
rerankingQueriesFromContext.length == 0);
String transformerFeatureStore =
SolrQueryRequestContextUtils.getFvStoreName(req);
- Map<String, String[]> transformerExternalFeatureInfo =
LTRQParserPlugin.extractEFIParams(localparams);
+ Map<String, String[]> transformerExternalFeatureInfo =
+ LTRQParserPlugin.extractEFIParams(localparams);
final LoggingModel loggingModel =
createLoggingModel(transformerFeatureStore);
- setupRerankingQueriesForLogging(transformerFeatureStore,
transformerExternalFeatureInfo, loggingModel);
+ setupRerankingQueriesForLogging(
+ transformerFeatureStore, transformerExternalFeatureInfo,
loggingModel);
setupRerankingWeightsForLogging(context);
}
/**
- * The loggingModel is an empty model that is just used to extract the
features
- * and log them
+ * The loggingModel is an empty model that is just used to extract the
features and log them
+ *
* @param transformerFeatureStore the explicit transformer feature store
*/
private LoggingModel createLoggingModel(String transformerFeatureStore) {
final ManagedFeatureStore fr =
ManagedFeatureStore.getManagedFeatureStore(req.getCore());
final FeatureStore store = fr.getFeatureStore(transformerFeatureStore);
- transformerFeatureStore = store.getName(); // if transformerFeatureStore
was null before this gets actual name
+ transformerFeatureStore =
+ store.getName(); // if transformerFeatureStore was null before this
gets actual name
- return new LoggingModel(loggingModelName,
- transformerFeatureStore, store.getFeatures());
+ return new LoggingModel(loggingModelName, transformerFeatureStore,
store.getFeatures());
}
/**
* When preparing the reranking queries for logging features various
scenarios apply:
- *
- * No Reranking
- * There is the need of a logger model from the default feature store or
the explicit feature store passed
- * to extract the feature vector
- *
- * Re Ranking
- * 1) If no explicit feature store is passed, the models for each
reranking query can be safely re-used
- * the feature vector can be fetched from the feature vector cache.
- * 2) If an explicit feature store is passed, and no reranking query uses
a model with that feature store,
- * There is the need of a logger model to extract the feature vector
- * 3) If an explicit feature store is passed, and there is a reranking
query that uses a model with that feature store,
- * the model can be re-used and there is no need for a logging model
+ *
+ * <p>No Reranking There is the need of a logger model from the default
feature store or the
+ * explicit feature store passed to extract the feature vector
+ *
+ * <p>Re Ranking 1) If no explicit feature store is passed, the models for
each reranking query
+ * can be safely re-used the feature vector can be fetched from the
feature vector cache. 2) If
+ * an explicit feature store is passed, and no reranking query uses a
model with that feature
+ * store, There is the need of a logger model to extract the feature
vector 3) If an explicit
+ * feature store is passed, and there is a reranking query that uses a
model with that feature
+ * store, the model can be re-used and there is no need for a logging model
Review comment:
this comment auto-reformatting impairs content clarity.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/OriginalScoreFeature.java
##########
@@ -28,48 +27,56 @@
import org.apache.lucene.search.Weight;
import org.apache.solr.ltr.DocInfo;
import org.apache.solr.request.SolrQueryRequest;
+
/**
- * This feature returns the original score that the document had before
performing
- * the reranking.
+ * This feature returns the original score that the document had before
performing the reranking.
* Example configuration:
+ *
* <pre>{
- "name": "originalScore",
- "class": "org.apache.solr.ltr.feature.OriginalScoreFeature",
- "params": { }
-}</pre>
- **/
+ * "name": "originalScore",
+ * "class": "org.apache.solr.ltr.feature.OriginalScoreFeature",
+ * "params": { }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java
##########
@@ -209,96 +209,108 @@ public ModelWeight createWeight(IndexSearcher searcher,
ScoreMode scoreMode, flo
Collection<Feature> features = null;
if (this.extractAllFeatures) {
features = allFeatures;
+ } else {
+ features = modelFeatures;
}
- else{
- features = modelFeatures;
- }
- final Feature.FeatureWeight[] extractedFeatureWeights = new
Feature.FeatureWeight[features.size()];
+ final Feature.FeatureWeight[] extractedFeatureWeights =
+ new Feature.FeatureWeight[features.size()];
final Feature.FeatureWeight[] modelFeaturesWeights = new
Feature.FeatureWeight[modelFeatSize];
- List<Feature.FeatureWeight > featureWeights = new
ArrayList<>(features.size());
+ List<Feature.FeatureWeight> featureWeights = new
ArrayList<>(features.size());
if (querySemaphore == null) {
createWeights(searcher, scoreMode.needsScores(), featureWeights,
features);
- }
- else{
+ } else {
createWeightsParallel(searcher, scoreMode.needsScores(), featureWeights,
features);
}
- int i=0, j = 0;
+ int i = 0, j = 0;
if (this.extractAllFeatures) {
for (final Feature.FeatureWeight fw : featureWeights) {
extractedFeatureWeights[i++] = fw;
}
- for (final Feature f : modelFeatures){
- modelFeaturesWeights[j++] = extractedFeatureWeights[f.getIndex()]; //
we can lookup by featureid because all features will be extracted when
this.extractAllFeatures is set
+ for (final Feature f : modelFeatures) {
+ modelFeaturesWeights[j++] =
+ extractedFeatureWeights[
+ f.getIndex()]; // we can lookup by featureid because all
features will be
+ // extracted when this.extractAllFeatures is set
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java
##########
@@ -209,96 +209,108 @@ public ModelWeight createWeight(IndexSearcher searcher,
ScoreMode scoreMode, flo
Collection<Feature> features = null;
if (this.extractAllFeatures) {
features = allFeatures;
+ } else {
+ features = modelFeatures;
}
- else{
- features = modelFeatures;
- }
- final Feature.FeatureWeight[] extractedFeatureWeights = new
Feature.FeatureWeight[features.size()];
+ final Feature.FeatureWeight[] extractedFeatureWeights =
+ new Feature.FeatureWeight[features.size()];
final Feature.FeatureWeight[] modelFeaturesWeights = new
Feature.FeatureWeight[modelFeatSize];
- List<Feature.FeatureWeight > featureWeights = new
ArrayList<>(features.size());
+ List<Feature.FeatureWeight> featureWeights = new
ArrayList<>(features.size());
if (querySemaphore == null) {
createWeights(searcher, scoreMode.needsScores(), featureWeights,
features);
- }
- else{
+ } else {
createWeightsParallel(searcher, scoreMode.needsScores(), featureWeights,
features);
}
- int i=0, j = 0;
+ int i = 0, j = 0;
if (this.extractAllFeatures) {
for (final Feature.FeatureWeight fw : featureWeights) {
extractedFeatureWeights[i++] = fw;
}
- for (final Feature f : modelFeatures){
- modelFeaturesWeights[j++] = extractedFeatureWeights[f.getIndex()]; //
we can lookup by featureid because all features will be extracted when
this.extractAllFeatures is set
+ for (final Feature f : modelFeatures) {
+ modelFeaturesWeights[j++] =
+ extractedFeatureWeights[
+ f.getIndex()]; // we can lookup by featureid because all
features will be
+ // extracted when this.extractAllFeatures is set
}
- }
- else{
- for (final Feature.FeatureWeight fw: featureWeights){
+ } else {
+ for (final Feature.FeatureWeight fw : featureWeights) {
extractedFeatureWeights[i++] = fw;
modelFeaturesWeights[j++] = fw;
}
}
return new ModelWeight(modelFeaturesWeights, extractedFeatureWeights,
allFeatures.size());
}
- private void createWeights(IndexSearcher searcher, boolean needsScores,
- List<Feature.FeatureWeight > featureWeights, Collection<Feature>
features) throws IOException {
+ private void createWeights(
+ IndexSearcher searcher,
+ boolean needsScores,
+ List<Feature.FeatureWeight> featureWeights,
+ Collection<Feature> features)
+ throws IOException {
final SolrQueryRequest req = getRequest();
// since the feature store is a linkedhashmap order is preserved
for (final Feature f : features) {
- try{
+ try {
Feature.FeatureWeight fw = f.createWeight(searcher, needsScores, req,
originalQuery, efi);
featureWeights.add(fw);
} catch (final Exception e) {
- throw new RuntimeException("Exception from createWeight for " +
f.toString() + " "
- + e.getMessage(), e);
+ throw new RuntimeException(
+ "Exception from createWeight for " + f.toString() + " " +
e.getMessage(), e);
}
}
}
- private class CreateWeightCallable implements
Callable<Feature.FeatureWeight>{
- final private Feature f;
- final private IndexSearcher searcher;
- final private boolean needsScores;
- final private SolrQueryRequest req;
+ private class CreateWeightCallable implements
Callable<Feature.FeatureWeight> {
+ private final Feature f;
+ private final IndexSearcher searcher;
+ private final boolean needsScores;
+ private final SolrQueryRequest req;
- public CreateWeightCallable(Feature f, IndexSearcher searcher, boolean
needsScores, SolrQueryRequest req){
+ public CreateWeightCallable(
+ Feature f, IndexSearcher searcher, boolean needsScores,
SolrQueryRequest req) {
this.f = f;
this.searcher = searcher;
this.needsScores = needsScores;
this.req = req;
}
@Override
- public Feature.FeatureWeight call() throws Exception{
+ public Feature.FeatureWeight call() throws Exception {
try {
- Feature.FeatureWeight fw = f.createWeight(searcher, needsScores, req,
originalQuery, efi);
+ Feature.FeatureWeight fw = f.createWeight(searcher, needsScores, req,
originalQuery, efi);
return fw;
} catch (final Exception e) {
- throw new RuntimeException("Exception from createWeight for " +
f.toString() + " "
- + e.getMessage(), e);
+ throw new RuntimeException(
+ "Exception from createWeight for " + f.toString() + " " +
e.getMessage(), e);
} finally {
querySemaphore.release();
ltrThreadMgr.releaseLTRSemaphore();
}
}
} // end of call CreateWeightCallable
- private void createWeightsParallel(IndexSearcher searcher, boolean
needsScores,
- List<Feature.FeatureWeight > featureWeights, Collection<Feature>
features) throws RuntimeException {
+ private void createWeightsParallel(
+ IndexSearcher searcher,
+ boolean needsScores,
+ List<Feature.FeatureWeight> featureWeights,
+ Collection<Feature> features)
+ throws RuntimeException {
final SolrQueryRequest req = getRequest();
- List<Future<Feature.FeatureWeight> > futures = new
ArrayList<>(features.size());
- try{
+ List<Future<Feature.FeatureWeight>> futures = new
ArrayList<>(features.size());
+ try {
for (final Feature f : features) {
CreateWeightCallable callable = new CreateWeightCallable(f, searcher,
needsScores, req);
RunnableFuture<Feature.FeatureWeight> runnableFuture = new
FutureTask<>(callable);
- querySemaphore.acquire(); // always acquire before the ltrSemaphore is
acquired, to guarantee a that the current query is within the limit for max.
threads
- ltrThreadMgr.acquireLTRSemaphore();//may block and/or interrupt
- ltrThreadMgr.execute(runnableFuture);//releases semaphore when done
+ querySemaphore
+ .acquire(); // always acquire before the ltrSemaphore is acquired,
to guarantee a that
+ // the current query is within the limit for max. threads
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/FieldValueFeature.java
##########
@@ -41,27 +40,29 @@
import org.apache.solr.search.SolrIndexSearcher;
/**
- * This feature returns the value of a field in the current document.
- * The field must have stored="true" or docValues="true" properties.
- * Example configuration:
+ * This feature returns the value of a field in the current document. The
field must have
+ * stored="true" or docValues="true" properties. Example configuration:
+ *
* <pre>{
- "name": "rawHits",
- "class": "org.apache.solr.ltr.feature.FieldValueFeature",
- "params": {
- "field": "hits"
- }
-}</pre>
+ * "name": "rawHits",
+ * "class": "org.apache.solr.ltr.feature.FieldValueFeature",
+ * "params": {
+ * "field": "hits"
+ * }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/FeatureLogger.java
##########
@@ -19,15 +19,18 @@
import org.apache.solr.search.SolrIndexSearcher;
/**
- * FeatureLogger can be registered in a model and provide a strategy for
logging
- * the feature values.
+ * FeatureLogger can be registered in a model and provide a strategy for
logging the feature values.
*/
public abstract class FeatureLogger {
- /** the name of the cache using for storing the feature value **/
+ /** the name of the cache using for storing the feature value * */
Review comment:
this change surprises me.
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/Feature.java
##########
@@ -37,63 +36,67 @@
import org.apache.solr.util.SolrPluginUtils;
/**
- * A recipe for computing a feature. Subclass this for specialized feature
calculations.
- * <p>
- * A feature consists of
+ * A recipe for computing a feature. Subclass this for specialized feature
calculations.
+ *
+ * <p>A feature consists of
+ *
* <ul>
- * <li> a name as the identifier
- * <li> parameters to represent the specific feature
+ * <li>a name as the identifier
+ * <li>parameters to represent the specific feature
* </ul>
- * <p>
- * Example configuration (snippet):
+ *
+ * <p>Example configuration (snippet):
+ *
* <pre>{
- "class" : "...",
- "name" : "myFeature",
- "params" : {
- ...
- }
-}</pre>
- * <p>
- * {@link Feature} is an abstract class and concrete classes should implement
- * the {@link #validate()} function, and must implement the {@link
#paramsToMap()}
- * and createWeight() methods.
+ * "class" : "...",
+ * "name" : "myFeature",
+ * "params" : {
+ * ...
+ * }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/ValueFeature.java
##########
@@ -19,31 +19,31 @@
import java.io.IOException;
import java.util.LinkedHashMap;
import java.util.Map;
-
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.search.DocIdSetIterator;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.solr.request.SolrQueryRequest;
+
/**
* This feature allows to return a constant given value for the current
document.
*
- * Example configuration:
+ * <p>Example configuration:
+ *
* <pre>{
- "name" : "userFromMobile",
- "class" : "org.apache.solr.ltr.feature.ValueFeature",
- "params" : { "value" : "${userFromMobile}", "required":true }
- }</pre>
+ * "name" : "userFromMobile",
+ * "class" : "org.apache.solr.ltr.feature.ValueFeature",
+ * "params" : { "value" : "${userFromMobile}", "required":true }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRScoringQuery.java
##########
@@ -420,16 +437,16 @@ private void setFeaturesInfo(){
}
/**
- * Goes through all the stored feature values, and calculates the
normalized
- * values for all the features that will be used for scoring.
- * Then calculate and return the model's score.
+ * Goes through all the stored feature values, and calculates the
normalized values for all the
+ * features that will be used for scoring. Then calculate and return the
model's score.
*/
private float makeNormalizedFeaturesAndScore() {
int pos = 0;
for (final Feature.FeatureWeight feature : modelFeatureWeights) {
final int featureId = feature.getIndex();
FeatureInfo fInfo = featuresInfo[featureId];
- if (fInfo.isUsed()) { // not checking for finfo == null as that would
be a bug we should catch
+ if (fInfo
+ .isUsed()) { // not checking for finfo == null as that would be a
bug we should catch
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/LTRThreadModule.java
##########
@@ -28,35 +27,38 @@
import org.apache.solr.util.plugin.NamedListInitializedPlugin;
/**
- * The LTRThreadModule is optionally used by the {@link
org.apache.solr.ltr.search.LTRQParserPlugin} and
- * {@link
org.apache.solr.ltr.response.transform.LTRFeatureLoggerTransformerFactory
LTRFeatureLoggerTransformerFactory}
- * classes to parallelize the creation of {@link
org.apache.solr.ltr.feature.Feature.FeatureWeight Feature.FeatureWeight}
- * objects.
- * <p>
- * Example configuration:
+ * The LTRThreadModule is optionally used by the {@link
org.apache.solr.ltr.search.LTRQParserPlugin}
+ * and {@link
org.apache.solr.ltr.response.transform.LTRFeatureLoggerTransformerFactory
+ * LTRFeatureLoggerTransformerFactory} classes to parallelize the creation of
{@link
+ * org.apache.solr.ltr.feature.Feature.FeatureWeight Feature.FeatureWeight}
objects.
+ *
+ * <p>Example configuration:
+ *
* <pre>
- <queryParser name="ltr"
class="org.apache.solr.ltr.search.LTRQParserPlugin">
- <int name="threadModule.totalPoolThreads">10</int>
- <int name="threadModule.numThreadsPerRequest">5</int>
- </queryParser>
-
- <transformer name="features"
class="org.apache.solr.ltr.response.transform.LTRFeatureLoggerTransformerFactory">
- <int name="threadModule.totalPoolThreads">10</int>
- <int name="threadModule.numThreadsPerRequest">5</int>
- </transformer>
-</pre>
- * If an individual solr instance is expected to receive no more than one
query at a time, it is best
- * to set <code>totalPoolThreads</code> and <code>numThreadsPerRequest</code>
to the same value.
+ * <queryParser name="ltr"
class="org.apache.solr.ltr.search.LTRQParserPlugin">
+ * <int name="threadModule.totalPoolThreads">10</int>
+ * <int name="threadModule.numThreadsPerRequest">5</int>
+ * </queryParser>
+ *
+ * <transformer name="features"
class="org.apache.solr.ltr.response.transform.LTRFeatureLoggerTransformerFactory">
+ * <int name="threadModule.totalPoolThreads">10</int>
+ * <int name="threadModule.numThreadsPerRequest">5</int>
+ * </transformer>
+ * </pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/SolrFeature.java
##########
@@ -41,22 +40,23 @@
import org.apache.solr.search.SyntaxError;
/**
- * This feature allows you to reuse any Solr query as a feature. The value
- * of the feature will be the score of the given query for the current
document.
- * See <a href="https://lucene.apache.org/solr/guide/other-parsers.html";>Solr
documentation of other parsers</a> you can use as a feature.
- * Example configurations:
+ * This feature allows you to reuse any Solr query as a feature. The value of
the feature will be
+ * the score of the given query for the current document. See <a
+ * href="https://lucene.apache.org/solr/guide/other-parsers.html";>Solr
documentation of other
+ * parsers</a> you can use as a feature. Example configurations:
+ *
* <pre>[{ "name": "isBook",
- "class": "org.apache.solr.ltr.feature.SolrFeature",
- "params":{ "fq": ["{!terms f=category}book"] }
-},
-{
- "name": "documentRecency",
- "class": "org.apache.solr.ltr.feature.SolrFeature",
- "params": {
- "q": "{!func}recip( ms(NOW,publish_date), 3.16e-11, 1, 1)"
- }
-}]</pre>
- **/
+ * "class": "org.apache.solr.ltr.feature.SolrFeature",
+ * "params":{ "fq": ["{!terms f=category}book"] }
+ * },
+ * {
+ * "name": "documentRecency",
+ * "class": "org.apache.solr.ltr.feature.SolrFeature",
+ * "params": {
+ * "q": "{!func}recip( ms(NOW,publish_date), 3.16e-11, 1, 1)"
+ * }
+ * }]</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/feature/FieldLengthFeature.java
##########
@@ -28,20 +27,23 @@
import org.apache.lucene.search.Query;
import org.apache.lucene.util.SmallFloat;
import org.apache.solr.request.SolrQueryRequest;
+
/**
- * This feature returns the length of a field (in terms) for the current
document.
- * Example configuration:
+ * This feature returns the length of a field (in terms) for the current
document. Example
+ * configuration:
+ *
* <pre>{
- "name": "titleLength",
- "class": "org.apache.solr.ltr.feature.FieldLengthFeature",
- "params": {
- "field": "title"
- }
-}</pre>
- * Note: since this feature relies on norms values that are stored in a single
byte
- * the value of the feature could have a lightly different value.
- * (see also {@link org.apache.lucene.search.similarities.ClassicSimilarity})
- **/
+ * "name": "titleLength",
+ * "class": "org.apache.solr.ltr.feature.FieldLengthFeature",
+ * "params": {
+ * "field": "title"
+ * }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/model/WrapperModel.java
##########
@@ -29,26 +28,26 @@
/**
* A scoring model that wraps the other model.
*
- * <p>This model loads a model from an external resource during the
initialization.
- * The way of fetching the wrapped model is depended on
- * the implementation of {@link WrapperModel#fetchModelMap()}.
+ * <p>This model loads a model from an external resource during the
initialization. The way of
+ * fetching the wrapped model is depended on the implementation of {@link
+ * WrapperModel#fetchModelMap()}.
*
- * <p>This model doesn't hold the actual parameters of the wrapped model,
- * thus it can manage large models which are difficult to upload to ZooKeeper.
+ * <p>This model doesn't hold the actual parameters of the wrapped model, thus
it can manage large
+ * models which are difficult to upload to ZooKeeper.
*
* <p>Example configuration:
+ *
* <pre>{
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/model/MultipleAdditiveTreesModel.java
##########
@@ -21,99 +21,102 @@
import java.util.List;
import java.util.Map;
import java.util.Stack;
-
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.search.Explanation;
import org.apache.solr.ltr.feature.Feature;
import org.apache.solr.ltr.norm.Normalizer;
import org.apache.solr.util.SolrPluginUtils;
/**
- * A scoring model that computes scores based on the summation of multiple
weighted trees.
- * Example models are LambdaMART and Gradient Boosted Regression Trees (GBRT) .
- * <p>
- * Example configuration:
-<pre>{
- "class" : "org.apache.solr.ltr.model.MultipleAdditiveTreesModel",
- "name" : "multipleadditivetreesmodel",
- "features":[
- { "name" : "userTextTitleMatch"},
- { "name" : "originalScore"}
- ],
- "params" : {
- "trees" : [
- {
- "weight" : "1",
- "root": {
- "feature" : "userTextTitleMatch",
- "threshold" : "0.5",
- "left" : {
- "value" : "-100"
- },
- "right" : {
- "feature" : "originalScore",
- "threshold" : "10.0",
- "left" : {
- "value" : "50"
- },
- "right" : {
- "value" : "75"
- }
- }
- }
- },
- {
- "weight" : "2",
- "root" : {
- "value" : "-10"
- }
- }
- ]
- }
-}</pre>
- * <p>
- * Training libraries:
+ * A scoring model that computes scores based on the summation of multiple
weighted trees. Example
+ * models are LambdaMART and Gradient Boosted Regression Trees (GBRT) .
+ *
+ * <p>Example configuration:
+ *
+ * <pre>{
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/interleaving/algorithms/TeamDraftInterleaving.java
##########
@@ -57,20 +57,18 @@
}
/**
- * Team Draft Interleaving considers two ranking models: modelA and modelB.
- * For a given query, each model returns its ranked list of documents La =
(a1,a2,...) and Lb = (b1, b2, ...).
- * The algorithm creates a unique ranked list I = (i1, i2, ...).
- * This list is created by interleaving elements from the two lists la and
lb as described by Chapelle et al.[1].
- * Each element Ij is labelled TeamA if it is selected from La and TeamB if
it is selected from Lb.
- * <p>
- * [1] O. Chapelle, T. Joachims, F. Radlinski, and Y. Yue.
- * Large-scale validation and analysis of interleaved search evaluation. ACM
TOIS, 30(1):1–41, Feb. (2012)
- * <p>
- * Assumptions:
- * - rerankedA and rerankedB has the same length.
- * They contains the same search results, ranked differently by two ranking
models
- * - each reranked list can not contain the same search result more than
once.
- * - results are all from the same shard
+ * Team Draft Interleaving considers two ranking models: modelA and modelB.
For a given query,
+ * each model returns its ranked list of documents La = (a1,a2,...) and Lb =
(b1, b2, ...). The
+ * algorithm creates a unique ranked list I = (i1, i2, ...). This list is
created by interleaving
+ * elements from the two lists la and lb as described by Chapelle et al.[1].
Each element Ij is
+ * labelled TeamA if it is selected from La and TeamB if it is selected from
Lb.
+ *
+ * <p>[1] O. Chapelle, T. Joachims, F. Radlinski, and Y. Yue. Large-scale
validation and analysis
+ * of interleaved search evaluation. ACM TOIS, 30(1):1–41, Feb. (2012)
+ *
+ * <p>Assumptions: - rerankedA and rerankedB has the same length. They
contains the same search
+ * results, ranked differently by two ranking models - each reranked list
can not contain the same
+ * search result more than once. - results are all from the same shard
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/model/DefaultWrapperModel.java
##########
@@ -35,32 +34,38 @@
/**
* A scoring model that fetches the wrapped model from {@link
SolrResourceLoader}.
*
- * <p>This model uses {@link SolrResourceLoader#openResource(String)} for
fetching the wrapped model.
- * If you give a relative path for {@code params/resource}, this model will
try to load the wrapped model from
- * the instance directory (i.e. ${solr.solr.home}). Otherwise, seek through
classpaths.
+ * <p>This model uses {@link SolrResourceLoader#openResource(String)} for
fetching the wrapped
+ * model. If you give a relative path for {@code params/resource}, this model
will try to load the
+ * wrapped model from the instance directory (i.e. ${solr.solr.home}).
Otherwise, seek through
+ * classpaths.
*
* <p>Example configuration:
+ *
* <pre>{
- "class": "org.apache.solr.ltr.model.DefaultWrapperModel",
- "name": "myWrapperModelName",
- "params": {
- "resource": "models/myModel.json"
- }
-}</pre>
+ * "class": "org.apache.solr.ltr.model.DefaultWrapperModel",
+ * "name": "myWrapperModelName",
+ * "params": {
+ * "resource": "models/myModel.json"
+ * }
+ * }</pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/norm/MinMaxNormalizer.java
##########
@@ -20,19 +20,22 @@
/**
* A Normalizer to scale a feature value using a (min,max) range.
- * <p>
- * Example configuration:
-<pre>
-"norm" : {
- "class" : "org.apache.solr.ltr.norm.MinMaxNormalizer",
- "params" : { "min":"0", "max":"50" }
-}
-</pre>
+ *
+ * <p>Example configuration:
+ *
+ * <pre>
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/model/LinearModel.java
##########
@@ -19,79 +19,85 @@
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
-
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.search.Explanation;
import org.apache.solr.ltr.feature.Feature;
import org.apache.solr.ltr.norm.Normalizer;
/**
- * A scoring model that computes scores using a dot product.
- * Example models are RankSVM and Pranking.
- * <p>
- * Example configuration:
+ * A scoring model that computes scores using a dot product. Example models
are RankSVM and
+ * Pranking.
+ *
+ * <p>Example configuration:
+ *
* <pre>{
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/interleaving/algorithms/TeamDraftInterleaving.java
##########
@@ -22,31 +22,31 @@
import java.util.LinkedList;
import java.util.Random;
import java.util.Set;
-
import org.apache.lucene.search.ScoreDoc;
import org.apache.solr.ltr.interleaving.Interleaving;
import org.apache.solr.ltr.interleaving.InterleavingResult;
/**
- * Interleaving was introduced the first time by Joachims in [1, 2].
- * Team Draft Interleaving is among the most successful and used interleaving
approaches[3].
- * Team Draft Interleaving implements a method similar to the way in which
captains select their players in team-matches.
- * Team Draft Interleaving produces a fair distribution of ranking models’
elements in the final interleaved list.
- * "Team draft interleaving" has also proved to overcome an issue of the
"Balanced interleaving" approach, in determining the winning model[4].
- * <p>
- * [1] T. Joachims. Optimizing search engines using clickthrough data. KDD
(2002)
- * [2]
T.Joachims.Evaluatingretrievalperformanceusingclickthroughdata.InJ.Franke, G.
Nakhaeizadeh, and I. Renz, editors,
- * Text Mining, pages 79–96. Physica/Springer (2003)
- * [3] F. Radlinski, M. Kurup, and T. Joachims. How does clickthrough data
reflect re-
- * trieval quality? In CIKM, pages 43–52. ACM Press (2008)
- * [4] O. Chapelle, T. Joachims, F. Radlinski, and Y. Yue.
- * Large-scale validation and analysis of interleaved search evaluation. ACM
TOIS, 30(1):1–41, Feb. (2012)
+ * Interleaving was introduced the first time by Joachims in [1, 2]. Team
Draft Interleaving is
+ * among the most successful and used interleaving approaches[3]. Team Draft
Interleaving implements
+ * a method similar to the way in which captains select their players in
team-matches. Team Draft
+ * Interleaving produces a fair distribution of ranking models’ elements in
the final interleaved
+ * list. "Team draft interleaving" has also proved to overcome an issue of the
"Balanced
+ * interleaving" approach, in determining the winning model[4].
+ *
+ * <p>[1] T. Joachims. Optimizing search engines using clickthrough data. KDD
(2002) [2]
+ * T.Joachims.Evaluatingretrievalperformanceusingclickthroughdata.InJ.Franke,
G. Nakhaeizadeh, and
+ * I. Renz, editors, Text Mining, pages 79–96. Physica/Springer (2003) [3] F.
Radlinski, M. Kurup,
+ * and T. Joachims. How does clickthrough data reflect re- trieval quality? In
CIKM, pages 43–52.
+ * ACM Press (2008) [4] O. Chapelle, T. Joachims, F. Radlinski, and Y. Yue.
Large-scale validation
+ * and analysis of interleaved search evaluation. ACM TOIS, 30(1):1–41, Feb.
(2012)
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/package-info.java
##########
@@ -16,30 +16,24 @@
*/
/**
- * <p>
- * This package contains the main logic for performing the reranking using
- * a Learning to Rank model.
- * </p>
- * <p>
- * A model will be applied on each document through a {@link
org.apache.solr.ltr.LTRScoringQuery}, a
- * subclass of {@link org.apache.lucene.search.Query}. As a normal query,
- * the learned model will produce a new score
- * for each document reranked.
- * </p>
- * <p>
- * A {@link org.apache.solr.ltr.LTRScoringQuery} is created by providing an
instance of
- * {@link org.apache.solr.ltr.model.LTRScoringModel}. An instance of
- * {@link org.apache.solr.ltr.model.LTRScoringModel}
- * defines how to combine the features in order to create a new
- * score for a document. A new Learning to Rank model is plugged
- * into the framework by extending {@link
org.apache.solr.ltr.model.LTRScoringModel},
- * (see for example {@link
org.apache.solr.ltr.model.MultipleAdditiveTreesModel} and {@link
org.apache.solr.ltr.model.LinearModel}).
- * </p>
- * <p>
- * The {@link org.apache.solr.ltr.LTRScoringQuery} will take care of computing
the values of
- * all the features (see {@link org.apache.solr.ltr.feature.Feature}) and then
will delegate the final score
- * generation to the {@link org.apache.solr.ltr.model.LTRScoringModel}, by
calling the method
- * {@link org.apache.solr.ltr.model.LTRScoringModel#score(float[]
modelFeatureValuesNormalized) score(float[] modelFeatureValuesNormalized)}.
- * </p>
+ * This package contains the main logic for performing the reranking using a
Learning to Rank model.
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/model/NeuralNetworkModel.java
##########
@@ -28,75 +27,79 @@
/**
* A scoring model that computes document scores using a neural network.
- * <p>
- * Supported <a
href="https://en.wikipedia.org/wiki/Activation_function";>activation
functions</a> are:
- * <code>identity</code>, <code>relu</code>, <code>sigmoid</code>,
<code>tanh</code>, <code>leakyrelu</code> and
- * contributions to support additional activation functions are welcome.
- * <p>
- * Example configuration:
-<pre>{
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/response/transform/LTRFeatureLoggerTransformerFactory.java
##########
@@ -162,31 +161,31 @@ private FeatureLogger createFeatureLogger(String
formatStr) {
class FeatureTransformer extends DocTransformer {
- final private String name;
- final private SolrParams localparams;
- final private SolrQueryRequest req;
- final private boolean hasExplicitFeatureStore;
+ private final String name;
+ private final SolrParams localparams;
+ private final SolrQueryRequest req;
+ private final boolean hasExplicitFeatureStore;
private List<LeafReaderContext> leafContexts;
private SolrIndexSearcher searcher;
/**
- * rerankingQueries, modelWeights have:
- * length=1 - [Classic LTR] When reranking with a single model
- * length=2 - [Interleaving] When reranking with interleaving (two ranking
models are involved)
+ * rerankingQueries, modelWeights have: length=1 - [Classic LTR] When
reranking with a single
+ * model length=2 - [Interleaving] When reranking with interleaving (two
ranking models are
+ * involved)
Review comment:
this comment auto-reformatting impairs content clarity.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/model/LTRScoringModel.java
##########
@@ -38,71 +37,81 @@
/**
* A scoring model computes scores that can be used to rerank documents.
- * <p>
- * A scoring model consists of
+ *
+ * <p>A scoring model consists of
+ *
* <ul>
- * <li> a list of features ({@link Feature}) and
- * <li> a list of normalizers ({@link Normalizer}) plus
- * <li> parameters or configuration to represent the scoring algorithm.
+ * <li>a list of features ({@link Feature}) and
+ * <li>a list of normalizers ({@link Normalizer}) plus
+ * <li>parameters or configuration to represent the scoring algorithm.
* </ul>
- * <p>
- * Example configuration (snippet):
+ *
+ * <p>Example configuration (snippet):
+ *
* <pre>{
Review comment:
note to self: check this is still rendered correctly
##########
File path: solr/contrib/ltr/src/java/org/apache/solr/ltr/store/FeatureStore.java
##########
@@ -20,16 +20,16 @@
import java.util.Collections;
import java.util.LinkedHashMap;
import java.util.List;
-
import org.apache.solr.ltr.feature.Feature;
import org.apache.solr.ltr.feature.FeatureException;
public class FeatureStore {
- /** the name of the default feature store **/
+ /** the name of the default feature store * */
public static final String DEFAULT_FEATURE_STORE_NAME = "_DEFAULT_";
- private final LinkedHashMap<String,Feature> store = new LinkedHashMap<>();
// LinkedHashMap because we need predictable iteration order
+ private final LinkedHashMap<String, Feature> store =
+ new LinkedHashMap<>(); // LinkedHashMap because we need predictable
iteration order
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/response/transform/LTRFeatureLoggerTransformerFactory.java
##########
@@ -51,18 +50,19 @@
import org.apache.solr.util.SolrPluginUtils;
/**
Review comment:
note to self: check this is still rendered correctly
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/store/rest/ManagedFeatureStore.java
##########
@@ -170,41 +162,41 @@ public void doGet(BaseSolrResource endpoint, String
childId) {
} else {
final FeatureStore store = getFeatureStore(childId);
if (store == null) {
- throw new SolrException(SolrException.ErrorCode.BAD_REQUEST,
- "missing feature store [" + childId + "]");
+ throw new SolrException(
+ SolrException.ErrorCode.BAD_REQUEST, "missing feature store [" +
childId + "]");
}
- response.add(FEATURES_JSON_FIELD,
- featuresAsManagedResources(store));
+ response.add(FEATURES_JSON_FIELD, featuresAsManagedResources(store));
}
}
private static List<Object> featuresAsManagedResources(FeatureStore store) {
final List<Feature> storedFeatures = store.getFeatures();
final List<Object> features = new ArrayList<Object>(storedFeatures.size());
for (final Feature f : storedFeatures) {
- final LinkedHashMap<String,Object> m = toFeatureMap(f);
+ final LinkedHashMap<String, Object> m = toFeatureMap(f);
m.put(FEATURE_STORE_NAME_KEY, store.getName());
features.add(m);
}
return features;
}
- private static LinkedHashMap<String,Object> toFeatureMap(Feature feat) {
- final LinkedHashMap<String,Object> o = new LinkedHashMap<>(4, 1.0f); // 1
extra for caller to add store
+ private static LinkedHashMap<String, Object> toFeatureMap(Feature feat) {
+ final LinkedHashMap<String, Object> o =
+ new LinkedHashMap<>(4, 1.0f); // 1 extra for caller to add store
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/response/transform/LTRFeatureLoggerTransformerFactory.java
##########
@@ -210,99 +209,120 @@ public void setContext(ResultContext context) {
searcher = context.getSearcher();
if (searcher == null) {
- throw new SolrException(
- SolrException.ErrorCode.BAD_REQUEST,
- "searcher is null");
+ throw new SolrException(SolrException.ErrorCode.BAD_REQUEST, "searcher
is null");
}
leafContexts = searcher.getTopReaderContext().leaves();
if (threadManager != null) {
-
threadManager.setExecutor(context.getRequest().getCore().getCoreContainer().getUpdateShardHandler().getUpdateExecutor());
+ threadManager.setExecutor(
+ context
+ .getRequest()
+ .getCore()
+ .getCoreContainer()
+ .getUpdateShardHandler()
+ .getUpdateExecutor());
}
rerankingQueriesFromContext =
SolrQueryRequestContextUtils.getScoringQueries(req);
- docsWereNotReranked = (rerankingQueriesFromContext == null ||
rerankingQueriesFromContext.length == 0);
+ docsWereNotReranked =
+ (rerankingQueriesFromContext == null ||
rerankingQueriesFromContext.length == 0);
String transformerFeatureStore =
SolrQueryRequestContextUtils.getFvStoreName(req);
- Map<String, String[]> transformerExternalFeatureInfo =
LTRQParserPlugin.extractEFIParams(localparams);
+ Map<String, String[]> transformerExternalFeatureInfo =
+ LTRQParserPlugin.extractEFIParams(localparams);
final LoggingModel loggingModel =
createLoggingModel(transformerFeatureStore);
- setupRerankingQueriesForLogging(transformerFeatureStore,
transformerExternalFeatureInfo, loggingModel);
+ setupRerankingQueriesForLogging(
+ transformerFeatureStore, transformerExternalFeatureInfo,
loggingModel);
setupRerankingWeightsForLogging(context);
}
/**
- * The loggingModel is an empty model that is just used to extract the
features
- * and log them
+ * The loggingModel is an empty model that is just used to extract the
features and log them
+ *
* @param transformerFeatureStore the explicit transformer feature store
*/
private LoggingModel createLoggingModel(String transformerFeatureStore) {
final ManagedFeatureStore fr =
ManagedFeatureStore.getManagedFeatureStore(req.getCore());
final FeatureStore store = fr.getFeatureStore(transformerFeatureStore);
- transformerFeatureStore = store.getName(); // if transformerFeatureStore
was null before this gets actual name
+ transformerFeatureStore =
+ store.getName(); // if transformerFeatureStore was null before this
gets actual name
Review comment:
perhaps moving the comment to a separate line would be clearer here too.
##########
File path:
solr/contrib/ltr/src/java/org/apache/solr/ltr/norm/StandardNormalizer.java
##########
@@ -20,20 +20,22 @@
/**
* A Normalizer to scale a feature value around an
average-and-standard-deviation distribution.
- * <p>
- * Example configuration:
-<pre>
-"norm" : {
- "class" : "org.apache.solr.ltr.norm.StandardNormalizer",
- "params" : { "avg":"42", "std":"6" }
-}
-</pre>
- * <p>
- * Example normalizations:
+ *
+ * <p>Example configuration:
+ *
+ * <pre>
Review comment:
note to self: check this is still rendered correctly
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