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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.solr.handler.component;

import com.google.common.hash.HashFunction;
import com.tdunning.math.stats.AVLTreeDigest;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.nio.charset.StandardCharsets;
import java.util.Arrays;
import java.util.Collection;
import java.util.Date;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
import java.util.TreeSet;
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.queries.function.FunctionValues;
import org.apache.lucene.queries.function.ValueSource;
import org.apache.lucene.util.BytesRef;
import org.apache.solr.common.EnumFieldValue;
import org.apache.solr.common.SolrException;
import org.apache.solr.common.util.NamedList;
import org.apache.solr.common.util.SimpleOrderedMap;
import org.apache.solr.handler.component.StatsField.Stat;
import org.apache.solr.schema.AbstractEnumField;
import org.apache.solr.schema.DatePointField;
import org.apache.solr.schema.FieldType;
import org.apache.solr.schema.PointField;
import org.apache.solr.schema.SchemaField;
import org.apache.solr.schema.StrField;
import org.apache.solr.schema.TrieDateField;
import org.apache.solr.schema.TrieField;
import org.apache.solr.util.hll.HLL;
import org.apache.solr.util.hll.HLLType;

/** Factory class for creating instance of {@link org.apache.solr.handler.component.StatsValues} */
public class StatsValuesFactory {

  /**
   * Creates an instance of StatsValues which supports values from the specified {@link StatsField}
   *
   * @param statsField {@link StatsField} whose statistics will be created by the resulting {@link
   *     StatsValues}
   * @return Instance of {@link StatsValues} that will create statistics from values from the
   *     specified {@link StatsField}
   */
  public static StatsValues createStatsValues(StatsField statsField) {

    final SchemaField sf = statsField.getSchemaField();

    if (null == sf) {
      // function stats
      return new NumericStatsValues(statsField);
    }

    final FieldType fieldType = sf.getType(); // TODO: allow FieldType to provide impl.

    if (TrieDateField.class.isInstance(fieldType) || DatePointField.class.isInstance(fieldType)) {
      DateStatsValues statsValues = new DateStatsValues(statsField);
      if (sf.multiValued()) {
        return new SortedDateStatsValues(statsValues, statsField);
      }
      return statsValues;
    } else if (TrieField.class.isInstance(fieldType) || PointField.class.isInstance(fieldType)) {

      NumericStatsValues statsValue = new NumericStatsValues(statsField);
      if (sf.multiValued()) {
        return new SortedNumericStatsValues(statsValue, statsField);
      }
      return statsValue;
    } else if (StrField.class.isInstance(fieldType)) {
      return new StringStatsValues(statsField);
    } else if (AbstractEnumField.class.isInstance(fieldType)) {
      return new EnumStatsValues(statsField);
    } else {
      throw new SolrException(
          SolrException.ErrorCode.BAD_REQUEST,
          "Field type " + fieldType + " is not currently supported");
    }
  }

  /**
   * Abstract implementation of {@link StatsValues} that provides the default behavior for most
   * StatsValues implementations.
   *
   * 
There are very few requirements placed on what statistics concrete implementations should
   * collect, with the only required statistics being the minimum and maximum values.
   */
  private abstract static class AbstractStatsValues implements StatsValues {
    private static final String FACETS = "facets";

    /** Tracks all data about tthe stats we need to collect */
    protected final StatsField statsField;

    /** may be null if we are collecting stats directly from a function ValueSource */
    protected final SchemaField sf;

    /** may be null if we are collecting stats directly from a function ValueSource */
    protected final FieldType ft;

    // final booleans from StatsField to allow better inlining & JIT optimizing
    protected final boolean computeCount;
    protected final boolean computeMissing;
    protected final boolean
        computeCalcDistinct; // needed for either countDistinct or distinctValues
    protected final boolean computeMin;
    protected final boolean computeMax;
    protected final boolean computeMinOrMax;
    protected final boolean computeCardinality;

    /**
     * Either a function value source to collect from, or the ValueSource associated with a single
     * valued field we are collecting from. Will be null until/unless {@link #setNextReader} is
     * called at least once
     */
    private ValueSource valueSource;

    /**
     * Context to use when retrieving FunctionValues, will be null until/unless {@link
     * #setNextReader} is called at least once
     */
    private Map vsContext;

    /**
     * Values to collect, will be null until/unless {@link #setNextReader} is called at least once
     */
    protected FunctionValues values;

    protected T max;
    protected T min;
    protected long missing;
    protected long count;
    protected long countDistinct;
    protected final Set distinctValues;

    /** Hash function that must be used by implementations of {@link #hash} */
    protected final HashFunction hasher;

    // if null, no HLL logic can be computed; not final because of "union" optimization (see below)
    private HLL hll;

    // facetField facetValue
    protected Map> facets = new HashMap<>();

    protected AbstractStatsValues(StatsField statsField) {
      this.statsField = statsField;
      this.computeCount = statsField.calculateStats(Stat.count);
      this.computeMissing = statsField.calculateStats(Stat.missing);
      this.computeCalcDistinct =
          statsField.calculateStats(Stat.countDistinct)
              || statsField.calculateStats(Stat.distinctValues);
      this.computeMin = statsField.calculateStats(Stat.min);
      this.computeMax = statsField.calculateStats(Stat.max);
      this.computeMinOrMax = computeMin || computeMax;

      this.distinctValues = computeCalcDistinct ? new TreeSet<>() : null;

      this.computeCardinality = statsField.calculateStats(Stat.cardinality);
      if (computeCardinality) {

        hasher = statsField.getHllOptions().getHasher();
        hll = statsField.getHllOptions().newHLL();
        assert null != hll : "Cardinality requires an HLL";
      } else {
        hll = null;
        hasher = null;
      }

      // alternatively, we could refactor a common base class that doesn't know/care
      // about either SchemaField or ValueSource - but then there would be a lot of
      // duplicate code between "NumericSchemaFieldStatsValues" and
      // "NumericValueSourceStatsValues" which would have diff parent classes
      //
      // part of the complexity here being that the StatsValues API serves two
      // leaders: collecting concrete Values from things like DocValuesStats and
      // the distributed aggregation logic, but also collecting docIds which it
      // then
      // uses to go out and pull concreate values from the ValueSource
      // (from a func, or single valued field)
      if (null != statsField.getSchemaField()) {
        assert null == statsField.getValueSource();
        this.sf = statsField.getSchemaField();
        this.ft = sf.getType();
      } else {
        assert null != statsField.getValueSource();
        assert null == statsField.getSchemaField();
        this.sf = null;
        this.ft = null;
      }
    }

    @Override
    @SuppressWarnings({"unchecked"})
    public void accumulate(NamedList stv) {
      if (computeCount) {
        count += (Long) stv.get("count");
      }
      if (computeMissing) {
        missing += (Long) stv.get("missing");
      }
      if (computeCalcDistinct) {
        distinctValues.addAll((Collection) stv.get("distinctValues"));
        countDistinct = distinctValues.size();
      }

      if (computeMinOrMax) {
        updateMinMax((T) stv.get("min"), (T) stv.get("max"));
      }

      if (computeCardinality) {
        byte[] data = (byte[]) stv.get("cardinality");
        HLL other = HLL.fromBytes(data);
        if (hll.getType().equals(HLLType.EMPTY)) {
          // The HLL.union method goes out of it's way not to modify the "other" HLL.
          // Which means in the case of merging into an "EMPTY" HLL (garunteed to happen at
          // least once in every coordination of shard requests) it always clones all
          // of the internal storage -- but since we're going to throw "other" away after
          // the merge, this just means a short term doubling of RAM that we can skip.
          hll = other;
        } else {
          hll.union(other);
        }
      }

      updateTypeSpecificStats(stv);

      NamedList f = (NamedList) stv.get(FACETS);
      if (f == null) {
        return;
      }

      for (int i = 0; i < f.size(); i++) {
        String field = f.getName(i);
        NamedList vals = (NamedList) f.getVal(i);
        Map addTo = facets.get(field);
        if (addTo == null) {
          addTo = new HashMap<>();
          facets.put(field, addTo);
        }
        for (int j = 0; j < vals.size(); j++) {
          String val = vals.getName(j);
          StatsValues vvals = addTo.get(val);
          if (vvals == null) {
            vvals = createStatsValues(statsField);
            addTo.put(val, vvals);
          }
          vvals.accumulate((NamedList) vals.getVal(j));
        }
      }
    }

    @Override
    @SuppressWarnings({"unchecked"})
    public void accumulate(BytesRef value, int count) {
      if (null == ft) {
        throw new IllegalStateException(
            "Can't collect & convert BytesRefs on stats that do't use a a FieldType: "
                + statsField);
      }
      T typedValue = (T) ft.toObject(sf, value);
      accumulate(typedValue, count);
    }

    public void accumulate(T value, int count) {
      assert null != value : "Can't accumulate null";

      if (computeCount) {
        this.count += count;
      }
      if (computeCalcDistinct) {
        distinctValues.add(value);
        countDistinct = distinctValues.size();
      }
      if (computeMinOrMax) {
        updateMinMax(value, value);
      }
      if (computeCardinality) {
        if (null == hasher) {
          assert value instanceof Number : "pre-hashed value support only works with numeric longs";
          hll.addRaw(((Number) value).longValue());
        } else {
          hll.addRaw(hash(value));
        }
      }
      updateTypeSpecificStats(value, count);
    }

    @Override
    public void missing() {
      if (computeMissing) {
        missing++;
      }
    }

    @Override
    public void addMissing(int count) {
      missing += count;
    }

    @Override
    public void addFacet(String facetName, Map facetValues) {
      facets.put(facetName, facetValues);
    }

    @Override
    public NamedList getStatsValues() {
      NamedList res = new SimpleOrderedMap<>();

      if (statsField.includeInResponse(Stat.min)) {
        res.add("min", min);
      }
      if (statsField.includeInResponse(Stat.max)) {
        res.add("max", max);
      }
      if (statsField.includeInResponse(Stat.count)) {
        res.add("count", count);
      }
      if (statsField.includeInResponse(Stat.missing)) {
        res.add("missing", missing);
      }
      if (statsField.includeInResponse(Stat.distinctValues)) {
        res.add("distinctValues", distinctValues);
      }
      if (statsField.includeInResponse(Stat.countDistinct)) {
        res.add("countDistinct", countDistinct);
      }
      if (statsField.includeInResponse(Stat.cardinality)) {
        if (statsField.getIsShard()) {
          res.add("cardinality", hll.toBytes());
        } else {
          res.add("cardinality", hll.cardinality());
        }
      }

      addTypeSpecificStats(res);

      if (!facets.isEmpty()) {

        // add the facet stats
        NamedList> nl = new SimpleOrderedMap<>();
        for (Map.Entry> entry : facets.entrySet()) {
          NamedList> nl2 = new SimpleOrderedMap<>();
          nl.add(entry.getKey(), nl2);
          for (Map.Entry e2 : entry.getValue().entrySet()) {
            nl2.add(e2.getKey(), e2.getValue().getStatsValues());
          }
        }

        res.add(FACETS, nl);
      }

      return res;
    }

    @Override
    public void setNextReader(LeafReaderContext ctx) throws IOException {
      if (valueSource == null) {
        // first time we've collected local values, get the right ValueSource
        valueSource = (null == ft) ? statsField.getValueSource() : ft.getValueSource(sf, null);
        vsContext = ValueSource.newContext(statsField.getSearcher());
      }
      values = valueSource.getValues(vsContext, ctx);
    }

    /**
     * Hash function to be used for computing cardinality.
     *
     * 
This method will not be called in cases where the user has indicated the values are
     * already hashed. If this method is called, then {@link #hasher} will be non-null, and should
     * be used to generate the appropriate hash value.
     *
     * @see Stat#cardinality
     * @see #hasher
     */
    protected abstract long hash(T value);

    /**
     * Updates the minimum and maximum statistics based on the given values
     *
     * @param min Value that the current minimum should be updated against
     * @param max Value that the current maximum should be updated against
     */
    protected abstract void updateMinMax(T min, T max);

    /**
     * Updates the type specific statistics based on the given value
     *
     * @param value Value the statistics should be updated against
     * @param count Number of times the value is being accumulated
     */
    protected abstract void updateTypeSpecificStats(T value, int count);

    /**
     * Updates the type specific statistics based on the values in the given list
     *
     * @param stv List containing values the current statistics should be updated against
     */
    protected abstract void updateTypeSpecificStats(NamedList stv);

    /**
     * Add any type specific statistics to the given NamedList
     *
     * @param res NamedList to add the type specific statistics too
     */
    protected abstract void addTypeSpecificStats(NamedList res);
  }

  /** Implementation of StatsValues that supports Double values */
  static class NumericStatsValues extends AbstractStatsValues {

    double sum;
    double sumOfSquares;

    AVLTreeDigest tdigest;

    double minD; // perf optimization, only valid if (null != this.min)
    double maxD; // perf optimization, only valid if (null != this.max)

    protected final boolean computeSum;
    protected final boolean computeSumOfSquares;
    protected final boolean computePercentiles;

    public NumericStatsValues(StatsField statsField) {
      super(statsField);

      this.computeSum = statsField.calculateStats(Stat.sum);
      this.computeSumOfSquares = statsField.calculateStats(Stat.sumOfSquares);

      this.computePercentiles = statsField.calculateStats(Stat.percentiles);
      if (computePercentiles) {
        tdigest = new AVLTreeDigest(statsField.getTdigestCompression());
      }
    }

    @Override
    public long hash(Number v) {
      // have to use a bit of reflection to ensure good hash values since
      // we don't have truely type specific stats
      if (v instanceof Long) {
        return hasher.hashLong(v.longValue()).asLong();
      } else if (v instanceof Integer) {
        return hasher.hashInt(v.intValue()).asLong();
      } else if (v instanceof Double) {
        return hasher.hashLong(Double.doubleToRawLongBits(v.doubleValue())).asLong();
      } else if (v instanceof Float) {
        return hasher.hashInt(Float.floatToRawIntBits(v.floatValue())).asLong();
      } else if (v instanceof Byte) {
        return hasher.newHasher().putByte(v.byteValue()).hash().asLong();
      } else if (v instanceof Short) {
        return hasher.newHasher().putShort(v.shortValue()).hash().asLong();
      }
      // else...
      throw new SolrException(
          SolrException.ErrorCode.SERVER_ERROR,
          "Unsupported Numeric Type (" + v.getClass() + ") for hashing: " + statsField);
    }

    @Override
    public void accumulate(int docID) throws IOException {
      if (values.exists(docID)) {
        Number value = (Number) values.objectVal(docID);
        accumulate(value, 1);
      } else {
        missing();
      }
    }

    @Override
    public void updateTypeSpecificStats(NamedList stv) {
      if (computeSum) {
        sum += ((Number) stv.get("sum")).doubleValue();
      }
      if (computeSumOfSquares) {
        sumOfSquares += ((Number) stv.get("sumOfSquares")).doubleValue();
      }

      if (computePercentiles) {
        byte[] data = (byte[]) stv.get("percentiles");
        ByteBuffer buf = ByteBuffer.wrap(data);
        tdigest.add(AVLTreeDigest.fromBytes(buf));
      }
    }

    @Override
    public void updateTypeSpecificStats(Number v, int count) {
      double value = v.doubleValue();
      if (computeSumOfSquares) {
        sumOfSquares += (value * value * count); // for std deviation
      }
      if (computeSum) {
        sum += value * count;
      }
      if (computePercentiles) {
        tdigest.add(value, count);
      }
    }

    @Override
    protected void updateMinMax(Number min, Number max) {
      // we always use the double values, because that way the response Object class is
      // consistent regardless of whether we only have 1 value or many that we min/max
      //
      // TODO: would be nice to have subclasses for each type of Number ... breaks backcompat

      if (computeMin) { // nested if to encourage JIT to optimize aware final var?
        if (null != min) {
          double minD = min.doubleValue();
          if (null == this.min || minD < this.minD) {
            // Double for result & cached primitive double to minimize unboxing in future
            // comparisons
            this.min = this.minD = minD;
          }
        }
      }
      if (computeMax) { // nested if to encourage JIT to optimize aware final var?
        if (null != max) {
          double maxD = max.doubleValue();
          if (null == this.max || this.maxD < maxD) {
            // Double for result & cached primitive double to minimize unboxing in future
            // comparisons
            this.max = this.maxD = maxD;
          }
        }
      }
    }

    /**
     * Adds sum, sumOfSquares, mean, stddev, and percentiles to the given NamedList
     *
     * @param res NamedList to add the type specific statistics too
     */
    @Override
    protected void addTypeSpecificStats(NamedList res) {
      if (statsField.includeInResponse(Stat.sum)) {
        res.add("sum", sum);
      }
      if (statsField.includeInResponse(Stat.sumOfSquares)) {
        res.add("sumOfSquares", sumOfSquares);
      }
      if (statsField.includeInResponse(Stat.mean)) {
        res.add("mean", sum / count);
      }
      if (statsField.includeInResponse(Stat.stddev)) {
        res.add("stddev", getStandardDeviation());
      }
      if (statsField.includeInResponse(Stat.percentiles)) {
        if (statsField.getIsShard()) {
          // as of current t-digest version, smallByteSize() internally does a full conversion in
          // order to determine what the size is (can't be precomputed?) .. so rather then
          // serialize to a ByteBuffer twice, allocate the max possible size buffer,
          // serialize once, and then copy only the byte[] subset that we need, and free up the
          // buffer
          ByteBuffer buf = ByteBuffer.allocate(tdigest.byteSize()); // upper bound
          tdigest.asSmallBytes(buf);
          res.add("percentiles", Arrays.copyOf(buf.array(), buf.position()));
        } else {
          NamedList percentileNameList = new NamedList();
          for (Double percentile : statsField.getPercentilesList()) {
            // Empty document set case
            if (tdigest.size() == 0) {
              percentileNameList.add(percentile.toString(), null);
            } else {
              Double cutoff = tdigest.quantile(percentile / 100);
              percentileNameList.add(percentile.toString(), cutoff);
            }
          }
          res.add("percentiles", percentileNameList);
        }
      }
    }

    /**
     * Calculates the standard deviation statistic
     *
     * @return Standard deviation statistic
     */
    private double getStandardDeviation() {
      if (count <= 1.0D) {
        return 0.0D;
      }

      return Math.sqrt(((count * sumOfSquares) - (sum * sum)) / (count * (count - 1.0D)));
    }
  }

  /** Implementation of StatsValues that supports EnumField values */
  private static class EnumStatsValues extends AbstractStatsValues {

    public EnumStatsValues(StatsField statsField) {
      super(statsField);
    }

    @Override
    public long hash(EnumFieldValue v) {
      return hasher.hashInt(v.toInt().intValue()).asLong();
    }

    @Override
    public void accumulate(int docID) throws IOException {
      if (values.exists(docID)) {
        Integer intValue = (Integer) values.objectVal(docID);
        String stringValue = values.strVal(docID);
        EnumFieldValue enumFieldValue = new EnumFieldValue(intValue, stringValue);
        accumulate(enumFieldValue, 1);
      } else {
        missing();
      }
    }

    @Override
    protected void updateMinMax(EnumFieldValue min, EnumFieldValue max) {
      if (computeMin) { // nested if to encourage JIT to optimize aware final var?
        if (null != min) {
          if (null == this.min || (min.compareTo(this.min) < 0)) {
            this.min = min;
          }
        }
      }
      if (computeMax) { // nested if to encourage JIT to optimize aware final var?
        if (null != max) {
          if (null == this.max || (max.compareTo(this.max) > 0)) {
            this.max = max;
          }
        }
      }
    }

    @Override
    protected void updateTypeSpecificStats(NamedList stv) {
      // No type specific stats
    }

    @Override
    protected void updateTypeSpecificStats(EnumFieldValue value, int count) {
      // No type specific stats
    }

    /** Adds no type specific statistics */
    @Override
    protected void addTypeSpecificStats(NamedList res) {
      // Add no statistics
    }
  }

  /** /** Implementation of StatsValues that supports Date values */
  static class DateStatsValues extends AbstractStatsValues {

    private double sum = 0.0;
    double sumOfSquares = 0;

    protected final boolean computeSum;
    protected final boolean computeSumOfSquares;

    public DateStatsValues(StatsField statsField) {
      super(statsField);
      this.computeSum = statsField.calculateStats(Stat.sum);
      this.computeSumOfSquares = statsField.calculateStats(Stat.sumOfSquares);
    }

    @Override
    public long hash(Date v) {
      return hasher.hashLong(v.getTime()).asLong();
    }

    @Override
    public void accumulate(int docID) throws IOException {
      if (values.exists(docID)) {
        accumulate((Date) values.objectVal(docID), 1);
      } else {
        missing();
      }
    }

    @Override
    protected void updateTypeSpecificStats(NamedList stv) {
      if (computeSum) {
        sum += ((Number) stv.get("sum")).doubleValue();
      }
      if (computeSumOfSquares) {
        sumOfSquares += ((Number) stv.get("sumOfSquares")).doubleValue();
      }
    }

    @Override
    public void updateTypeSpecificStats(Date v, int count) {
      long value = v.getTime();
      if (computeSumOfSquares) {
        sumOfSquares += ((double) value * value * count); // for std deviation
      }
      if (computeSum) {
        sum += value * count;
      }
    }

    @Override
    protected void updateMinMax(Date min, Date max) {
      if (computeMin) { // nested if to encourage JIT to optimize aware final var?
        if (null != min && (this.min == null || this.min.after(min))) {
          this.min = min;
        }
      }
      if (computeMax) { // nested if to encourage JIT to optimize aware final var?
        if (null != max && (this.max == null || this.max.before(max))) {
          this.max = max;
        }
      }
    }

    /**
     * Adds sum and mean statistics to the given NamedList
     *
     * @param res NamedList to add the type specific statistics too
     */
    @Override
    protected void addTypeSpecificStats(NamedList res) {
      if (statsField.includeInResponse(Stat.sum)) {
        res.add("sum", sum);
      }
      if (statsField.includeInResponse(Stat.mean)) {
        res.add("mean", (count > 0) ? new Date((long) (sum / count)) : null);
      }
      if (statsField.includeInResponse(Stat.sumOfSquares)) {
        res.add("sumOfSquares", sumOfSquares);
      }
      if (statsField.includeInResponse(Stat.stddev)) {
        res.add("stddev", getStandardDeviation());
      }
    }

    /**
     * Calculates the standard deviation. For dates, this is really the MS deviation
     *
     * @return Standard deviation statistic
     */
    private double getStandardDeviation() {
      if (count <= 1) {
        return 0.0D;
      }
      return Math.sqrt(((count * sumOfSquares) - (sum * sum)) / (count * (count - 1.0D)));
    }
  }

  /** Implementation of StatsValues that supports String values */
  private static class StringStatsValues extends AbstractStatsValues {

    public StringStatsValues(StatsField statsField) {
      super(statsField);
    }

    @Override
    public long hash(String v) {
      return hasher.hashString(v, StandardCharsets.UTF_8).asLong();
    }

    @Override
    public void accumulate(int docID) throws IOException {
      if (values.exists(docID)) {
        String value = values.strVal(docID);
        if (value != null) {
          accumulate(value, 1);
        } else {
          missing();
        }
      } else {
        missing();
      }
    }

    @Override
    protected void updateTypeSpecificStats(NamedList stv) {
      // No type specific stats
    }

    @Override
    protected void updateTypeSpecificStats(String value, int count) {
      // No type specific stats
    }

    @Override
    protected void updateMinMax(String min, String max) {
      if (computeMin) { // nested if to encourage JIT to optimize aware final var?
        this.min = min(this.min, min);
      }
      if (computeMax) { // nested if to encourage JIT to optimize aware final var?
        this.max = max(this.max, max);
      }
    }

    /** Adds no type specific statistics */
    @Override
    protected void addTypeSpecificStats(NamedList res) {
      // Add no statistics
    }

    /**
     * Determines which of the given Strings is the maximum, as computed by {@link
     * String#compareTo(String)}
     *
     * @param str1 String to compare against b
     * @param str2 String compared against a
     * @return str1 if it is considered greater by {@link String#compareTo(String)}, str2 otherwise
     */
    private static String max(String str1, String str2) {
      if (str1 == null) {
        return str2;
      } else if (str2 == null) {
        return str1;
      }
      return (str1.compareTo(str2) > 0) ? str1 : str2;
    }

    /**
     * Determines which of the given Strings is the minimum, as computed by {@link
     * String#compareTo(String)}
     *
     * @param str1 String to compare against b
     * @param str2 String compared against a
     * @return str1 if it is considered less by {@link String#compareTo(String)}, str2 otherwise
     */
    private static String min(String str1, String str2) {
      if (str1 == null) {
        return str2;
      } else if (str2 == null) {
        return str1;
      }
      return (str1.compareTo(str2) < 0) ? str1 : str2;
    }
  }
}
 















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