Support min/max values for metadata query (#2208)

docs/content/design/broker.md

@@ -25,7 +25,7 @@ To determine which nodes to forward queries to, the Broker node first builds a v
 Caching
 -------
 
-Broker nodes employ a cache with a LRU cache invalidation strategy. The broker cache stores per segment results. The cache can be local to each broker node or shared across multiple nodes using an external distributed cache such as [memcached](http://memcached.org/). Each time a broker node receives a query, it first maps the query to a set of segments. A subset of these segment results may already exist in the cache and the results can be directly pulled from the cache. For any segment results that do not exist in the cache, the broker node will forward the query to the
+Broker nodes employ a cache with a LRU cache invalidation strategy. The broker cache stores per-segment results. The cache can be local to each broker node or shared across multiple nodes using an external distributed cache such as [memcached](http://memcached.org/). Each time a broker node receives a query, it first maps the query to a set of segments. A subset of these segment results may already exist in the cache and the results can be directly pulled from the cache. For any segment results that do not exist in the cache, the broker node will forward the query to the
 historical nodes. Once the historical nodes return their results, the broker will store those results in the cache. Real-time segments are never cached and hence requests for real-time data will always be forwarded to real-time nodes. Real-time data is perpetually changing and caching the results would be unreliable.
 
 HTTP Endpoints

docs/content/design/index.md

@@ -90,7 +90,7 @@ Druid is a column store, which means each individual column is stored separately
 in that query, and Druid is pretty good about only scanning exactly what it needs for a query.
 Different columns can also employ different compression methods. Different columns can also have different indexes associated with them.
 
-Druid indexes data on a per shard (segment) level.
+Druid indexes data on a per-shard (segment) level.
 
 ## Loading the Data
 

docs/content/querying/segmentmetadataquery.md

@@ -2,9 +2,10 @@
 layout: doc_page
 ---
 # Segment Metadata Queries
-Segment metadata queries return per segment information about:
+Segment metadata queries return per-segment information about:
 
 * Cardinality of all columns in the segment
+* Min/max values of string type columns in the segment
 * Estimated byte size for the segment columns if they were stored in a flat format
 * Number of rows stored inside the segment
 * Interval the segment covers
@@ -103,13 +104,17 @@ This is a list of properties that determines the amount of information returned
 
 By default, all analysis types will be used. If a property is not needed, omitting it from this list will result in a more efficient query.
 
-There are four types of column analyses:
+There are five types of column analyses:
 
 #### cardinality
 
 * `cardinality` in the result will return the estimated floor of cardinality for each column. Only relevant for
 dimension columns.
 
+#### minmax
+
+* Estimated min/max values for each column. Only relevant for dimension columns.
+
 #### size
 
 * `size` in the result will contain the estimated total segment byte size as if the data were stored in text format

processing/src/main/java/io/druid/query/metadata/SegmentAnalyzer.java

@@ -21,14 +21,21 @@ package io.druid.query.metadata;
 
 import com.google.common.base.Function;
 import com.google.common.base.Preconditions;
+import com.google.common.base.Strings;
 import com.google.common.collect.Iterables;
 import com.google.common.collect.Maps;
 import com.google.common.collect.Sets;
 import com.google.common.primitives.Longs;
 import com.metamx.common.StringUtils;
+import com.metamx.common.guava.Accumulator;
+import com.metamx.common.guava.Sequence;
 import com.metamx.common.logger.Logger;
+import io.druid.granularity.QueryGranularity;
+import io.druid.query.dimension.DefaultDimensionSpec;
 import io.druid.query.metadata.metadata.ColumnAnalysis;
 import io.druid.query.metadata.metadata.SegmentMetadataQuery;
+import io.druid.segment.Cursor;
+import io.druid.segment.DimensionSelector;
 import io.druid.segment.QueryableIndex;
 import io.druid.segment.Segment;
 import io.druid.segment.StorageAdapter;
@@ -38,8 +45,10 @@ import io.druid.segment.column.ColumnCapabilities;
 import io.druid.segment.column.ColumnCapabilitiesImpl;
 import io.druid.segment.column.ComplexColumn;
 import io.druid.segment.column.ValueType;
+import io.druid.segment.data.IndexedInts;
 import io.druid.segment.serde.ComplexMetricSerde;
 import io.druid.segment.serde.ComplexMetrics;
+import org.joda.time.Interval;
 
 import javax.annotation.Nullable;
 import java.util.EnumSet;
@@ -104,7 +113,11 @@ public class SegmentAnalyzer
           analysis = analyzeNumericColumn(capabilities, length, NUM_BYTES_IN_TEXT_FLOAT);
           break;
         case STRING:
-          analysis = analyzeStringColumn(capabilities, column, storageAdapter.getDimensionCardinality(columnName));
+          if (index != null) {
+            analysis = analyzeStringColumn(capabilities, column);
+          } else {
+            analysis = analyzeStringColumn(capabilities, storageAdapter, columnName);
+          }
           break;
         case COMPLEX:
           analysis = analyzeComplexColumn(capabilities, column, storageAdapter.getColumnTypeName(columnName));
@@ -140,6 +153,11 @@ public class SegmentAnalyzer
     return analysisTypes.contains(SegmentMetadataQuery.AnalysisType.CARDINALITY);
   }
 
+  public boolean analyzingMinMax()
+  {
+    return analysisTypes.contains(SegmentMetadataQuery.AnalysisType.MINMAX);
+  }
+
   private ColumnAnalysis analyzeNumericColumn(
       final ColumnCapabilities capabilities,
       final int length,
@@ -161,28 +179,30 @@ public class SegmentAnalyzer
         capabilities.hasMultipleValues(),
         size,
         null,
+        null,
+        null,
         null
     );
   }
 
   private ColumnAnalysis analyzeStringColumn(
       final ColumnCapabilities capabilities,
-      @Nullable final Column column,
+      final Column column
-      final int cardinality
   )
   {
     long size = 0;
 
-    if (column != null && analyzingSize()) {
+    Comparable min = null;
-      if (!capabilities.hasBitmapIndexes()) {
+    Comparable max = null;
-        return ColumnAnalysis.error("string_no_bitmap");
-      }
 
-      final BitmapIndex bitmapIndex = column.getBitmapIndex();
+    if (!capabilities.hasBitmapIndexes()) {
-      if (cardinality != bitmapIndex.getCardinality()) {
+      return ColumnAnalysis.error("string_no_bitmap");
-        return ColumnAnalysis.error("bitmap_wrong_cardinality");
+    }
-      }
 
+    final BitmapIndex bitmapIndex = column.getBitmapIndex();
+    final int cardinality = bitmapIndex.getCardinality();
+
+    if (analyzingSize()) {
       for (int i = 0; i < cardinality; ++i) {
         String value = bitmapIndex.getValue(i);
         if (value != null) {
@@ -191,11 +211,91 @@ public class SegmentAnalyzer
       }
     }
 
+    if (analyzingMinMax() && cardinality > 0) {
+      min = Strings.nullToEmpty(bitmapIndex.getValue(0));
+      max = Strings.nullToEmpty(bitmapIndex.getValue(cardinality - 1));
+    }
+
     return new ColumnAnalysis(
         capabilities.getType().name(),
         capabilities.hasMultipleValues(),
         size,
         analyzingCardinality() ? cardinality : 0,
+        min,
+        max,
+        null
+    );
+  }
+
+  private ColumnAnalysis analyzeStringColumn(
+      final ColumnCapabilities capabilities,
+      final StorageAdapter storageAdapter,
+      final String columnName
+  )
+  {
+    int cardinality = 0;
+    long size = 0;
+
+    Comparable min = null;
+    Comparable max = null;
+
+    if (analyzingCardinality()) {
+      cardinality = storageAdapter.getDimensionCardinality(columnName);
+    }
+
+    if (analyzingSize()) {
+      final long start = storageAdapter.getMinTime().getMillis();
+      final long end = storageAdapter.getMaxTime().getMillis();
+
+      final Sequence<Cursor> cursors =
+          storageAdapter.makeCursors(null, new Interval(start, end), QueryGranularity.ALL, false);
+
+      size = cursors.accumulate(
+          0L,
+          new Accumulator<Long, Cursor>()
+          {
+            @Override
+            public Long accumulate(Long accumulated, Cursor cursor)
+            {
+              DimensionSelector selector = cursor.makeDimensionSelector(
+                  new DefaultDimensionSpec(
+                      columnName,
+                      columnName
+                  )
+              );
+              if (selector == null) {
+                return accumulated;
+              }
+              long current = accumulated;
+              while (!cursor.isDone()) {
+                final IndexedInts vals = selector.getRow();
+                for (int i = 0; i < vals.size(); ++i) {
+                  final String dimVal = selector.lookupName(vals.get(i));
+                  if (dimVal != null && !dimVal.isEmpty()) {
+                    current += StringUtils.toUtf8(dimVal).length;
+                  }
+                }
+                cursor.advance();
+              }
+
+              return current;
+            }
+          }
+      );
+    }
+
+    if (analyzingMinMax()) {
+      min = storageAdapter.getMinValue(columnName);
+      max = storageAdapter.getMaxValue(columnName);
+    }
+
+    return new ColumnAnalysis(
+        capabilities.getType().name(),
+        capabilities.hasMultipleValues(),
+        size,
+        cardinality,
+        min,
+        max,
         null
     );
   }
@@ -218,7 +318,7 @@ public class SegmentAnalyzer
 
       final Function<Object, Long> inputSizeFn = serde.inputSizeFn();
       if (inputSizeFn == null) {
-        return new ColumnAnalysis(typeName, hasMultipleValues, 0, null, null);
+        return new ColumnAnalysis(typeName, hasMultipleValues, 0, null, null, null, null);
       }
 
       final int length = column.getLength();
@@ -232,6 +332,8 @@ public class SegmentAnalyzer
         hasMultipleValues,
         size,
         null,
+        null,
+        null,
         null
     );
   }

processing/src/main/java/io/druid/query/metadata/metadata/ColumnAnalysis.java

@@ -21,6 +21,7 @@ package io.druid.query.metadata.metadata;
 
 import com.fasterxml.jackson.annotation.JsonCreator;
 import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonTypeInfo;
 
 import java.util.Objects;
 
@@ -32,13 +33,15 @@ public class ColumnAnalysis
 
   public static ColumnAnalysis error(String reason)
   {
-    return new ColumnAnalysis("STRING", false, -1, null, ERROR_PREFIX + reason);
+    return new ColumnAnalysis("STRING", false, -1, null, null, null, ERROR_PREFIX + reason);
   }
 
   private final String type;
   private final boolean hasMultipleValues;
   private final long size;
   private final Integer cardinality;
+  private final Comparable minValue;
+  private final Comparable maxValue;
   private final String errorMessage;
 
   @JsonCreator
@@ -47,6 +50,8 @@ public class ColumnAnalysis
       @JsonProperty("hasMultipleValues") boolean hasMultipleValues,
       @JsonProperty("size") long size,
       @JsonProperty("cardinality") Integer cardinality,
+      @JsonProperty("minValue") Comparable minValue,
+      @JsonProperty("maxValue") Comparable maxValue,
       @JsonProperty("errorMessage") String errorMessage
   )
   {
@@ -54,6 +59,8 @@ public class ColumnAnalysis
     this.hasMultipleValues = hasMultipleValues;
     this.size = size;
     this.cardinality = cardinality;
+    this.minValue = minValue;
+    this.maxValue = maxValue;
     this.errorMessage = errorMessage;
   }
 
@@ -81,6 +88,20 @@ public class ColumnAnalysis
     return cardinality;
   }
 
+  @JsonTypeInfo(use = JsonTypeInfo.Id.NAME)
+  @JsonProperty
+  public Comparable getMinValue()
+  {
+    return minValue;
+  }
+
+  @JsonTypeInfo(use = JsonTypeInfo.Id.NAME)
+  @JsonProperty
+  public Comparable getMaxValue()
+  {
+    return maxValue;
+  }
+
   @JsonProperty
   public String getErrorMessage()
   {
@@ -113,21 +134,29 @@ public class ColumnAnalysis
     Integer cardinality = getCardinality();
     final Integer rhsCardinality = rhs.getCardinality();
     if (cardinality == null) {
-
       cardinality = rhsCardinality;
-    } else {
+    } else if (rhsCardinality != null) {
-      if (rhsCardinality != null) {
+      cardinality = Math.max(cardinality, rhsCardinality);
-        cardinality = Math.max(cardinality, rhsCardinality);
-      }
     }
 
-    return new ColumnAnalysis(
+    final boolean multipleValues = hasMultipleValues || rhs.isHasMultipleValues();
-        type,
+
-        hasMultipleValues || rhs.isHasMultipleValues(),
+    Comparable newMin = choose(minValue, rhs.minValue, false);
-        size + rhs.getSize(),
+    Comparable newMax = choose(maxValue, rhs.maxValue, true);
-        cardinality,
+
-        null
+    return new ColumnAnalysis(type, multipleValues, size + rhs.getSize(), cardinality, newMin, newMax, null);
-    );
+  }
+
+  private <T extends Comparable> T choose(T obj1, T obj2, boolean max)
+  {
+    if (obj1 == null) {
+      return max ? obj2 : null;
+    }
+    if (obj2 == null) {
+      return max ? obj1 : null;
+    }
+    int compare = max ? obj1.compareTo(obj2) : obj2.compareTo(obj1);
+    return compare > 0 ? obj1 : obj2;
   }
 
   @Override
@@ -138,6 +167,8 @@ public class ColumnAnalysis
            ", hasMultipleValues=" + hasMultipleValues +
            ", size=" + size +
            ", cardinality=" + cardinality +
+           ", minValue=" + minValue +
+           ", maxValue=" + maxValue +
            ", errorMessage='" + errorMessage + '\'' +
            '}';
   }
@@ -156,12 +187,14 @@ public class ColumnAnalysis
            size == that.size &&
            Objects.equals(type, that.type) &&
            Objects.equals(cardinality, that.cardinality) &&
+           Objects.equals(minValue, that.minValue) &&
+           Objects.equals(maxValue, that.maxValue) &&
            Objects.equals(errorMessage, that.errorMessage);
   }
 
   @Override
   public int hashCode()
   {
-    return Objects.hash(type, hasMultipleValues, size, cardinality, errorMessage);
+    return Objects.hash(type, hasMultipleValues, size, cardinality, minValue, maxValue, errorMessage);
   }
 }

processing/src/main/java/io/druid/query/metadata/metadata/SegmentMetadataQuery.java

@@ -53,7 +53,8 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
     CARDINALITY,
     SIZE,
     INTERVAL,
-    AGGREGATORS;
+    AGGREGATORS,
+    MINMAX;
 
     @JsonValue
     @Override
@@ -81,7 +82,8 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
   public static final EnumSet<AnalysisType> DEFAULT_ANALYSIS_TYPES = EnumSet.of(
       AnalysisType.CARDINALITY,
       AnalysisType.SIZE,
-      AnalysisType.INTERVAL
+      AnalysisType.INTERVAL,
+      AnalysisType.MINMAX
   );
 
   private final ColumnIncluderator toInclude;
@@ -177,6 +179,11 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
     return analysisTypes.contains(AnalysisType.AGGREGATORS);
   }
 
+  public boolean hasMinMax()
+  {
+    return analysisTypes.contains(AnalysisType.MINMAX);
+  }
+
   public byte[] getAnalysisTypesCacheKey()
   {
     int size = 1;
@@ -242,6 +249,20 @@ public class SegmentMetadataQuery extends BaseQuery<SegmentAnalysis>
     );
   }
 
+  public Query<SegmentAnalysis> withColumns(ColumnIncluderator includerator)
+  {
+    return new SegmentMetadataQuery(
+        getDataSource(),
+        getQuerySegmentSpec(),
+        includerator,
+        merge,
+        getContext(),
+        analysisTypes,
+        usingDefaultInterval,
+        lenientAggregatorMerge
+    );
+  }
+
   @Override
   public String toString()
   {

processing/src/main/java/io/druid/segment/QueryableIndexStorageAdapter.java

@@ -35,6 +35,7 @@ import io.druid.query.QueryInterruptedException;
 import io.druid.query.dimension.DimensionSpec;
 import io.druid.query.extraction.ExtractionFn;
 import io.druid.query.filter.Filter;
+import io.druid.segment.column.BitmapIndex;
 import io.druid.segment.column.Column;
 import io.druid.segment.column.ColumnCapabilities;
 import io.druid.segment.column.ComplexColumn;
@@ -140,6 +141,28 @@ public class QueryableIndexStorageAdapter implements StorageAdapter
     }
   }
 
+  @Override
+  public Comparable getMinValue(String dimension)
+  {
+    Column column = index.getColumn(dimension);
+    if (column != null && column.getCapabilities().hasBitmapIndexes()) {
+      BitmapIndex bitmap = column.getBitmapIndex();
+      return bitmap.getCardinality() > 0 ? bitmap.getValue(0) : null;
+    }
+    return null;
+  }
+
+  @Override
+  public Comparable getMaxValue(String dimension)
+  {
+    Column column = index.getColumn(dimension);
+    if (column != null && column.getCapabilities().hasBitmapIndexes()) {
+      BitmapIndex bitmap = column.getBitmapIndex();
+      return bitmap.getCardinality() > 0 ? bitmap.getValue(bitmap.getCardinality() - 1) : null;
+    }
+    return null;
+  }
+
   @Override
   public Capabilities getCapabilities()
   {

processing/src/main/java/io/druid/segment/StorageAdapter.java

@@ -44,6 +44,8 @@ public interface StorageAdapter extends CursorFactory
   public int getDimensionCardinality(String column);
   public DateTime getMinTime();
   public DateTime getMaxTime();
+  public Comparable getMinValue(String column);
+  public Comparable getMaxValue(String column);
   public Capabilities getCapabilities();
   public ColumnCapabilities getColumnCapabilities(String column);
 

processing/src/main/java/io/druid/segment/incremental/IncrementalIndex.java

@@ -51,6 +51,7 @@ import io.druid.segment.column.Column;
 import io.druid.segment.column.ColumnCapabilities;
 import io.druid.segment.column.ColumnCapabilitiesImpl;
 import io.druid.segment.column.ValueType;
+import io.druid.segment.data.Indexed;
 import io.druid.segment.data.IndexedInts;
 import io.druid.segment.serde.ComplexMetricExtractor;
 import io.druid.segment.serde.ComplexMetricSerde;
@@ -847,6 +848,10 @@ public abstract class IncrementalIndex<AggregatorType> implements Iterable<Row>,
 
     public int size();
 
+    public String getMinValue();
+
+    public String getMaxValue();
+
     public int add(String value);
 
     public SortedDimLookup sort();
@@ -899,6 +904,18 @@ public abstract class IncrementalIndex<AggregatorType> implements Iterable<Row>,
       return delegate.size();
     }
 
+    @Override
+    public String getMinValue()
+    {
+      return Strings.nullToEmpty(delegate.getMinValue());
+    }
+
+    @Override
+    public String getMaxValue()
+    {
+      return Strings.nullToEmpty(delegate.getMaxValue());
+    }
+
     @Override
     public int add(String value)
     {

processing/src/main/java/io/druid/segment/incremental/IncrementalIndexStorageAdapter.java

@@ -136,6 +136,20 @@ public class IncrementalIndexStorageAdapter implements StorageAdapter
     return index.getMaxTime();
   }
 
+  @Override
+  public Comparable getMinValue(String column)
+  {
+    IncrementalIndex.DimDim dimDim = index.getDimensionValues(column);
+    return dimDim == null ? null : dimDim.getMinValue();
+  }
+
+  @Override
+  public Comparable getMaxValue(String column)
+  {
+    IncrementalIndex.DimDim dimDim = index.getDimensionValues(column);
+    return dimDim == null ? null : dimDim.getMaxValue();
+  }
+
   @Override
   public Capabilities getCapabilities()
   {

processing/src/main/java/io/druid/segment/incremental/OnheapIncrementalIndex.java

@@ -278,6 +278,8 @@ public class OnheapIncrementalIndex extends IncrementalIndex<Aggregator>
   static class OnHeapDimDim implements DimDim
   {
     private final Map<String, Integer> valueToId = Maps.newHashMap();
+    private String minValue = null;
+    private String maxValue = null;
 
     private final List<String> idToValue = Lists.newArrayList();
     private final Object lock;
@@ -326,10 +328,24 @@ public class OnheapIncrementalIndex extends IncrementalIndex<Aggregator>
         final int index = size();
         valueToId.put(value, index);
         idToValue.add(value);
+        minValue = minValue == null || minValue.compareTo(value) > 0 ? value : minValue;
+        maxValue = maxValue == null || maxValue.compareTo(value) < 0 ? value : maxValue;
         return index;
       }
     }
 
+    @Override
+    public String getMinValue()
+    {
+      return minValue;
+    }
+
+    @Override
+    public String getMaxValue()
+    {
+      return maxValue;
+    }
+
     public OnHeapDimLookup sort()
     {
       synchronized (lock) {

processing/src/test/java/io/druid/query/metadata/SegmentMetadataQueryQueryToolChestTest.java

@@ -63,7 +63,7 @@ public class SegmentMetadataQueryQueryToolChestTest
         new SegmentMetadataQueryQueryToolChest(null).getCacheStrategy(query);
 
     // Test cache key generation
-    byte[] expectedKey = {0x04, 0x01, (byte) 0xFF, 0x00, 0x01, 0x02};
+    byte[] expectedKey = {0x04, 0x01, (byte) 0xFF, 0x00, 0x01, 0x02, 0x04};
     byte[] actualKey = strategy.computeCacheKey(query);
     Assert.assertArrayEquals(expectedKey, actualKey);
 
@@ -79,6 +79,8 @@ public class SegmentMetadataQueryQueryToolChestTest
                 true,
                 10881,
                 1,
+                "preferred",
+                "preferred",
                 null
             )
         ), 71982,

processing/src/test/java/io/druid/query/metadata/SegmentMetadataQueryTest.java

@@ -153,14 +153,18 @@ public class SegmentMetadataQueryTest
                 false,
                 12090,
                 null,
+                null,
+                null,
                 null
             ),
             "placement",
             new ColumnAnalysis(
                 ValueType.STRING.toString(),
                 false,
-                mmap1 ? 10881 : 0,
+                mmap1 ? 10881 : 10764,
                 1,
+                "preferred",
+                "preferred",
                 null
             ),
             "index",
@@ -169,9 +173,11 @@ public class SegmentMetadataQueryTest
                 false,
                 9672,
                 null,
+                null,
+                null,
                 null
             )
-        ), mmap1 ? 71982 : 32643,
+        ), mmap1 ? 71982 : 72755,
         1209,
         null
     );
@@ -187,6 +193,8 @@ public class SegmentMetadataQueryTest
                 false,
                 12090,
                 null,
+                null,
+                null,
                 null
             ),
             "placement",
@@ -195,6 +203,8 @@ public class SegmentMetadataQueryTest
                 false,
                 mmap2 ? 10881 : 0,
                 1,
+                null,
+                null,
                 null
             ),
             "index",
@@ -203,9 +213,12 @@ public class SegmentMetadataQueryTest
                 false,
                 9672,
                 null,
+                null,
+                null,
                 null
             )
-        ), mmap2 ? 71982 : 32643,
+        // null_column will be included only for incremental index, which makes a little bigger result than expected
+        ), mmap2 ? 71982 : 72755,
         1209,
         null
     );
@@ -236,6 +249,8 @@ public class SegmentMetadataQueryTest
                 false,
                 0,
                 1,
+                null,
+                null,
                 null
             ),
             "placementish",
@@ -244,6 +259,8 @@ public class SegmentMetadataQueryTest
                 true,
                 0,
                 9,
+                null,
+                null,
                 null
             )
         ),
@@ -298,6 +315,8 @@ public class SegmentMetadataQueryTest
                 false,
                 0,
                 1,
+                null,
+                null,
                 null
             ),
             "quality_uniques",
@@ -306,6 +325,8 @@ public class SegmentMetadataQueryTest
                 false,
                 0,
                 null,
+                null,
+                null,
                 null
             )
         ),
@@ -349,6 +370,53 @@ public class SegmentMetadataQueryTest
 
   @Test
   public void testSegmentMetadataQueryWithDefaultAnalysisMerge()
+  {
+    ColumnAnalysis analysis = new ColumnAnalysis(
+        ValueType.STRING.toString(),
+        false,
+        (mmap1 ? 10881 : 10764) + (mmap2 ? 10881 : 10764),
+        1,
+        "preferred",
+        "preferred",
+        null
+    );
+    testSegmentMetadataQueryWithDefaultAnalysisMerge("placement", analysis);
+  }
+
+  @Test
+  public void testSegmentMetadataQueryWithDefaultAnalysisMerge2()
+  {
+    ColumnAnalysis analysis = new ColumnAnalysis(
+        ValueType.STRING.toString(),
+        false,
+        (mmap1 ? 6882 : 6808) + (mmap2 ? 6882 : 6808),
+        3,
+        "spot",
+        "upfront",
+        null
+    );
+    testSegmentMetadataQueryWithDefaultAnalysisMerge("market", analysis);
+  }
+
+  @Test
+  public void testSegmentMetadataQueryWithDefaultAnalysisMerge3()
+  {
+    ColumnAnalysis analysis = new ColumnAnalysis(
+        ValueType.STRING.toString(),
+        false,
+        (mmap1 ? 9765 : 9660) + (mmap2 ? 9765 : 9660),
+        9,
+        "automotive",
+        "travel",
+        null
+    );
+    testSegmentMetadataQueryWithDefaultAnalysisMerge("quality", analysis);
+  }
+
+  private void testSegmentMetadataQueryWithDefaultAnalysisMerge(
+      String column,
+      ColumnAnalysis analysis
+  )
   {
     SegmentAnalysis mergedSegmentAnalysis = new SegmentAnalysis(
         differentIds ? "merged" : "testSegment",
@@ -360,14 +428,8 @@ public class SegmentMetadataQueryTest
                 false,
                 12090 * 2,
                 null,
-                null
+                null,
-            ),
+                null,
-            "placement",
-            new ColumnAnalysis(
-                ValueType.STRING.toString(),
-                false,
-                10881 * ((mmap1 ? 1 : 0) + (mmap2 ? 1 : 0)),
-                1,
                 null
             ),
             "index",
@@ -376,8 +438,12 @@ public class SegmentMetadataQueryTest
                 false,
                 9672 * 2,
                 null,
+                null,
+                null,
                 null
-            )
+            ),
+            column,
+            analysis
         ),
         expectedSegmentAnalysis1.getSize() + expectedSegmentAnalysis2.getSize(),
         expectedSegmentAnalysis1.getNumRows() + expectedSegmentAnalysis2.getNumRows(),
@@ -400,12 +466,11 @@ public class SegmentMetadataQueryTest
         toolChest
     );
 
+    Query query = testQuery.withColumns(new ListColumnIncluderator(Arrays.asList("__time", "index", column)));
+
     TestHelper.assertExpectedObjects(
         ImmutableList.of(mergedSegmentAnalysis),
-        myRunner.run(
+        myRunner.run(query, Maps.newHashMap()),
-            testQuery,
-            Maps.newHashMap()
-        ),
         "failed SegmentMetadata merging query"
     );
     exec.shutdownNow();
@@ -424,6 +489,8 @@ public class SegmentMetadataQueryTest
                 false,
                 0,
                 0,
+                null,
+                null,
                 null
             )
         ),
@@ -482,6 +549,8 @@ public class SegmentMetadataQueryTest
                 false,
                 0,
                 0,
+                null,
+                null,
                 null
             )
         ),

processing/src/test/java/io/druid/query/metadata/metadata/ColumnAnalysisTest.java

@@ -19,75 +19,149 @@
 
 package io.druid.query.metadata.metadata;
 
+import com.fasterxml.jackson.databind.ObjectMapper;
+import io.druid.segment.TestHelper;
 import org.junit.Assert;
 import org.junit.Test;
 
 public class ColumnAnalysisTest
 {
-  @Test
+  private final ObjectMapper MAPPER = TestHelper.getObjectMapper();
-  public void testFoldStringColumns()
+
+  private void assertSerDe(ColumnAnalysis analysis) throws Exception
   {
-    final ColumnAnalysis analysis1 = new ColumnAnalysis("STRING", false, 1L, 2, null);
+    Assert.assertEquals(analysis, MAPPER.readValue(MAPPER.writeValueAsString(analysis), ColumnAnalysis.class));
-    final ColumnAnalysis analysis2 = new ColumnAnalysis("STRING", true, 3L, 4, null);
-    final ColumnAnalysis expected = new ColumnAnalysis("STRING", true, 4L, 4, null);
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
   }
 
   @Test
-  public void testFoldWithNull()
+  public void testFoldStringColumns() throws Exception
   {
-    final ColumnAnalysis analysis1 = new ColumnAnalysis("STRING", false, 1L, 2, null);
+    final ColumnAnalysis analysis1 = new ColumnAnalysis("STRING", false, 1L, 2, "aaA", "Zzz", null);
+    final ColumnAnalysis analysis2 = new ColumnAnalysis("STRING", true, 3L, 4, "aAA", "ZZz", null);
+
+    assertSerDe(analysis1);
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis("STRING", true, 4L, 4, "aAA", "Zzz", null);
+
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
+  }
+
+  @Test
+  public void testFoldWithNull() throws Exception
+  {
+    final ColumnAnalysis analysis1 = new ColumnAnalysis("STRING", false, 1L, 2, null, null, null);
     Assert.assertEquals(analysis1, analysis1.fold(null));
+    assertSerDe(analysis1);
   }
 
   @Test
-  public void testFoldComplexColumns()
+  public void testFoldComplexColumns() throws Exception
   {
-    final ColumnAnalysis analysis1 = new ColumnAnalysis("hyperUnique", false, 0L, null, null);
+    final ColumnAnalysis analysis1 = new ColumnAnalysis("hyperUnique", false, 0L, null, null, null, null);
-    final ColumnAnalysis analysis2 = new ColumnAnalysis("hyperUnique", false, 0L, null, null);
+    final ColumnAnalysis analysis2 = new ColumnAnalysis("hyperUnique", false, 0L, null, null, null, null);
-    final ColumnAnalysis expected = new ColumnAnalysis("hyperUnique", false, 0L, null, null);
+
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
+    assertSerDe(analysis1);
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis("hyperUnique", false, 0L, null, null, null, null);
+
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
   }
 
   @Test
-  public void testFoldDifferentTypes()
+  public void testFoldDifferentTypes() throws Exception
   {
-    final ColumnAnalysis analysis1 = new ColumnAnalysis("hyperUnique", false, 1L, 1, null);
+    final ColumnAnalysis analysis1 = new ColumnAnalysis("hyperUnique", false, 1L, 1, null, null, null);
-    final ColumnAnalysis analysis2 = new ColumnAnalysis("COMPLEX", false, 2L, 2, null);
+    final ColumnAnalysis analysis2 = new ColumnAnalysis("COMPLEX", false, 2L, 2, null, null, null);
-    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, "error:cannot_merge_diff_types");
+
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
+    assertSerDe(analysis1);
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis(
+        "STRING",
+        false,
+        -1L,
+        null,
+        null,
+        null,
+        "error:cannot_merge_diff_types"
+    );
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
   }
 
   @Test
-  public void testFoldSameErrors()
+  public void testFoldSameErrors() throws Exception
   {
     final ColumnAnalysis analysis1 = ColumnAnalysis.error("foo");
     final ColumnAnalysis analysis2 = ColumnAnalysis.error("foo");
-    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, "error:foo");
+
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
+    assertSerDe(analysis1);
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, null, null, "error:foo");
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
   }
 
   @Test
-  public void testFoldErrorAndNoError()
+  public void testFoldErrorAndNoError() throws Exception
   {
     final ColumnAnalysis analysis1 = ColumnAnalysis.error("foo");
-    final ColumnAnalysis analysis2 = new ColumnAnalysis("STRING", false, 2L, 2, null);
+    final ColumnAnalysis analysis2 = new ColumnAnalysis("STRING", false, 2L, 2, "a", "z", null);
-    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, "error:foo");
+
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
+    assertSerDe(analysis1);
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, null, null, "error:foo");
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
   }
 
   @Test
-  public void testFoldDifferentErrors()
+  public void testFoldDifferentErrors() throws Exception
   {
     final ColumnAnalysis analysis1 = ColumnAnalysis.error("foo");
     final ColumnAnalysis analysis2 = ColumnAnalysis.error("bar");
-    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, "error:multiple_errors");
+
-    Assert.assertEquals(expected, analysis1.fold(analysis2));
+    assertSerDe(analysis1);
-    Assert.assertEquals(expected, analysis2.fold(analysis1));
+    assertSerDe(analysis2);
+
+    final ColumnAnalysis expected = new ColumnAnalysis("STRING", false, -1L, null, null, null, "error:multiple_errors");
+    ColumnAnalysis fold1 = analysis1.fold(analysis2);
+    ColumnAnalysis fold2 = analysis2.fold(analysis1);
+    Assert.assertEquals(expected, fold1);
+    Assert.assertEquals(expected, fold2);
+
+    assertSerDe(fold1);
+    assertSerDe(fold2);
   }
 }

publications/whitepaper/druid.tex

@@ -419,7 +419,7 @@ first maps the query to a set of segments. Results for certain segments may
 already exist in the cache and there is no need to recompute them. For any
 results that do not exist in the cache, the broker node will forward the query
 to the correct historical and real-time nodes. Once historical nodes return
-their results, the broker will cache these results on a per segment basis for
+their results, the broker will cache these results on a per-segment basis for
 future use. This process is illustrated in Figure~\ref{fig:caching}. Real-time
 data is never cached and hence requests for real-time data will always be
 forwarded to real-time nodes. Real-time data is perpetually changing and
@@ -428,7 +428,7 @@ caching the results is unreliable.
 \begin{figure*}
 \centering
 \includegraphics[width = 4.5in]{caching}
-\caption{Results are cached per segment. Queries combine cached results with results computed on historical and real-time nodes.}
+\caption{Results are cached per-segment. Queries combine cached results with results computed on historical and real-time nodes.}
 \label{fig:caching}
 \end{figure*}