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Mukund Thakur commented on HADOOP-18296: ---------------------------------------- Yes, it is. Although direct buffers are not used in Orc/Parquet. thinking if we should throw an Exception if the user is calling readVectored on direct buffers something like {code:java} class ChecksumFSInputChecker { ... ... @Override public void readVectored(List<? extends FileRange> ranges, IntFunction<ByteBuffer> allocate) throws IOException { if (allocate.apply(0).isDirect()) { throw new UnsupportedOperationException("Direct buffer is not supported"); } } }{code} cc [~ste...@apache.org] > Memory fragmentation in ChecksumFileSystem Vectored IO implementation. > ---------------------------------------------------------------------- > > Key: HADOOP-18296 > URL: https://issues.apache.org/jira/browse/HADOOP-18296 > Project: Hadoop Common > Issue Type: Sub-task > Components: common > Affects Versions: 3.4.0 > Reporter: Mukund Thakur > Priority: Minor > Labels: fs > > As we have implemented merging of ranges in the ChecksumFSInputChecker > implementation of vectored IO api, it can lead to memory fragmentation. Let > me explain by example. > > Suppose client requests for 3 ranges. > 0-500, 700-1000 and 1200-1500. > Now because of merging, all the above ranges will get merged into one and we > will allocate a big byte buffer of 0-1500 size but return sliced byte buffers > for the desired ranges. > Now once the client is done reading all the ranges, it will only be able to > free the memory for requested ranges and memory of the gaps will never be > released for eg here (500-700 and 1000-1200). > > Note this only happens for direct byte buffers. -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: common-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: common-issues-h...@hadoop.apache.org