[GitHub] [druid] kfaraz commented on a diff in pull request #13303: Hadoop based batch ingestion support range partition

["kfaraz (via GitHub)" <gi...@apache.org>]

kfaraz commented on code in PR #13303:
URL: https://github.com/apache/druid/pull/13303#discussion_r1092765726


##########
indexing-hadoop/src/main/java/org/apache/druid/indexer/DeterminePartitionsJob.java:
##########
@@ -346,10 +361,14 @@ protected void innerMap(
           rollupGranularity.bucketStart(inputRow.getTimestamp()).getMillis(),
           inputRow
       );
-      context.write(
-          new BytesWritable(HadoopDruidIndexerConfig.JSON_MAPPER.writeValueAsBytes(groupKey)),
-          NullWritable.get()
-      );
+
+      final byte[] bytes = HadoopDruidIndexerConfig.JSON_MAPPER.writeValueAsBytes(groupKey);
+      if (sample <= 1 || Math.abs(HASH_FUNCTION.hashBytes(bytes).asInt()) % sample == 0) {

Review Comment:
   Why are we using a hash of the bytes here? Doesn't this mean that we will never emit certain group keys?
   



##########
core/src/main/java/org/apache/druid/indexer/partitions/DimensionRangePartitionsSpec.java:
##########
@@ -144,6 +146,17 @@ public List<String> getPartitionDimensions()
     return partitionDimensions;
   }
 
+  public DimensionRangeShardSpec createShardSpec(

Review Comment:
   It is better to have this logic in `DeterminePartitionsJob` since it is only used there. You can check the number of dimensions and create either a `DimensionRangeShardSpec` or a `SingleDimensionShardSpec`.



##########
indexing-hadoop/src/main/java/org/apache/druid/indexer/DeterminePartitionsJob.java:
##########
@@ -346,10 +361,14 @@ protected void innerMap(
           rollupGranularity.bucketStart(inputRow.getTimestamp()).getMillis(),
           inputRow
       );
-      context.write(
-          new BytesWritable(HadoopDruidIndexerConfig.JSON_MAPPER.writeValueAsBytes(groupKey)),
-          NullWritable.get()
-      );
+
+      final byte[] bytes = HadoopDruidIndexerConfig.JSON_MAPPER.writeValueAsBytes(groupKey);
+      if (sample <= 1 || Math.abs(HASH_FUNCTION.hashBytes(bytes).asInt()) % sample == 0) {
+        context.write(

Review Comment:
   Nit: This can be put on a single-line now.



##########
indexing-hadoop/src/main/java/org/apache/druid/indexer/DeterminePartitionsJob.java:
##########
@@ -476,22 +502,29 @@ void emitDimValueCounts(
       final byte[] groupKey = buf.array();
 
       // Emit row-counter value.
-      write(context, groupKey, new DimValueCount("", "", 1));
-
-      for (final Map.Entry<String, Iterable<String>> dimAndValues : dims.entrySet()) {
-        final String dim = dimAndValues.getKey();
-
-        if (partitionDimension == null || partitionDimension.equals(dim)) {
-          final Iterable<String> dimValues = dimAndValues.getValue();
-
-          if (Iterables.size(dimValues) == 1) {
-            // Emit this value.
-            write(context, groupKey, new DimValueCount(dim, Iterables.getOnlyElement(dimValues), 1));
+      write(context, groupKey, new DimValueCount(Collections.emptyList(), StringTuple.create(), 1));
+
+      Iterator<List<String>> dimensionGroupIterator = dimensionGroupingSet.iterator();

Review Comment:
   Ah, I see it now. Thanks for the clarification. 
   
   In the case of single_dim too, I was wondering if we even need this check anymore. I don't think we can submit a spec with null partition dimension even for single_dim, atleast for index_parallel. There is a check in `ParallelIndexTuningConfig` which validates that partition dimensions are always specified. 
   
   We should have a similar check in `HadoopTuningConfig` too. Secretly choosing a partition dimension behind the scenes is probably not so great. It's better to fail if no partition dimension has been specified. What do you think?



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