zachjsh commented on code in PR #14319:
URL: https://github.com/apache/druid/pull/14319#discussion_r1203133006
##########
sql/src/main/java/org/apache/druid/sql/calcite/schema/SegmentMetadataCache.java:
##########
@@ -995,4 +986,118 @@ void doInLock(Runnable runnable)
runnable.run();
}
}
+
+
+ /**
+ * ColumnTypeMergePolicy defines the rules of which type to use when faced
with the possibility of different types
+ * for the same column from segment to segment. It is used to help compute a
{@link RowSignature} for a table in
+ * Druid based on the segment metadata of all segments, merging the types of
each column encountered to end up with
+ * a single type to represent it globally.
+ */
+ @JsonTypeInfo(use = JsonTypeInfo.Id.NAME, property = "type", defaultImpl =
LeastRestrictiveTypeMergePolicy.class)
+ @JsonSubTypes(value = {
+ @JsonSubTypes.Type(name = FirstTypeMergePolicy.NAME, value =
FirstTypeMergePolicy.class),
+ @JsonSubTypes.Type(name = LeastRestrictiveTypeMergePolicy.NAME, value =
LeastRestrictiveTypeMergePolicy.class)
+ })
+ @FunctionalInterface
+ public interface ColumnTypeMergePolicy
+ {
+ ColumnType merge(ColumnType existingType, ColumnType newType);
+ }
+
+ /**
+ * Classic logic, we use the first type we encounter. This policy is
effectively 'newest first' because we iterated
+ * segments starting from the most recent time chunk, so this typically
results in the most recently used type being
+ * chosen, at least for systems that are continuously updated with 'current'
data.
+ *
+ * Since {@link ColumnTypeMergePolicy} are used to compute the SQL schema,
at least in systems using SQL schemas which
+ * are partially or fully computed by this cache, this merge policy can
result in query time errors if incompatible
+ * types are mixed if the chosen type is more restrictive than the types of
some segments. If data is likely to vary
+ * in type across segments, consider using {@link
LeastRestrictiveTypeMergePolicy} instead.
+ */
+ public static class FirstTypeMergePolicy implements ColumnTypeMergePolicy
+ {
+ public static final String NAME = "latestInterval";
+ private static final FirstTypeMergePolicy INSTANCE = new
FirstTypeMergePolicy();
+
+ @Override
+ public ColumnType merge(ColumnType existingType, ColumnType newType)
+ {
+ if (existingType == null) {
+ return newType;
+ }
+ if (newType == null) {
+ return existingType;
+ }
+ // if any are json, are all json
+ if (ColumnType.NESTED_DATA.equals(newType) ||
ColumnType.NESTED_DATA.equals(existingType)) {
+ return ColumnType.NESTED_DATA;
+ }
+ // "existing type" is the 'newest' type, since we iterate the segments
list by newest start time
+ return existingType;
+ }
+
+ @Override
+ public int hashCode()
+ {
+ return Objects.hash(NAME);
+ }
+
+ @Override
+ public boolean equals(Object o)
+ {
+ if (this == o) {
+ return true;
+ }
+ return o != null && getClass() == o.getClass();
+ }
+
+ @Override
+ public String toString()
+ {
+ return NAME;
+ }
+ }
+
+ /**
+ * Resolves types using {@link ColumnType#leastRestrictiveType(ColumnType,
ColumnType)} to find the ColumnType that
+ * can best represent all data contained across all segments.
+ */
+ public static class LeastRestrictiveTypeMergePolicy implements
ColumnTypeMergePolicy
+ {
+ public static final String NAME = "leastRestrictive";
+
+ @Override
+ public ColumnType merge(ColumnType existingType, ColumnType newType)
+ {
+ try {
+ return ColumnType.leastRestrictiveType(existingType, newType);
+ }
+ catch (Types.IncompatibleTypeException incompatibleTypeException) {
+ // fall back to first encountered type if they are not compatible for
some reason
+ return FirstTypeMergePolicy.INSTANCE.merge(existingType, newType);
Review Comment:
Seems reasonable to me.
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