mukund-thakur commented on code in PR #999:
URL: https://github.com/apache/parquet-mr/pull/999#discussion_r993792933
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parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java:
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@@ -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:
Well, I just went through the code of ConsecutivePartList#readAll() again.
Yes, they are breaking the big range into smaller buffers but allocating all of
them in one go only, so won't the memory issue still persists?
Also, if I do the change in readAll() like I have already done the commented
readAllVectored(), we really won't be reducing the number of seek operations
thus won't be getting the real benefits of vectored IO. It will just be like
there is a big range to be fetched, we break into smaller ranges and fetch them
parallelly. ( This is similar to PARQUET-2149 which you proposed and have
already uploaded the PR :) ).
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