parthchandra commented on code in PR #999:
URL: https://github.com/apache/parquet-mr/pull/999#discussion_r993981829


##########
parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java:
##########
@@ -1093,10 +1099,38 @@ private ColumnChunkPageReadStore 
internalReadFilteredRowGroup(BlockMetaData bloc
         }
       }
     }
-    // actually read all the chunks
+    // Vectored IO up.
+
+    List<FileRange> ranges = new ArrayList<>();
     for (ConsecutivePartList consecutiveChunks : allParts) {
-      consecutiveChunks.readAll(f, builder);
+      ranges.add(FileRange.createFileRange(consecutiveChunks.offset, (int) 
consecutiveChunks.length));
+    }
+    LOG.warn("Doing vectored IO for ranges {}", ranges);
+    f.readVectored(ranges, ByteBuffer::allocate);

Review Comment:
   So if  I have  something like this - 
    `range 1, delta 1, range2`
   I will give you two ranges, `range1`, and `range2` separated by a gap of 
`delta1` bytes. If `delta1` is small enough, you will merge `range1` and 
`range2` and do a single scan. 
   If `range1` and `range2` are very large so that the resulting range is even 
larger, do you still do a single scan, or do you split the large range into 
smaller ranges and tradeoff some seek cost for increased parallelism?  
   



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