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ASF GitHub Bot commented on PARQUET-2149: ----------------------------------------- parthchandra commented on PR #968: URL: https://github.com/apache/parquet-mr/pull/968#issuecomment-1136528026 > Latency is the killer; in an HTTP request you want read enough but not discard data or break an http connection if the client suddenly does a seek() or readFully() somewhere else. file listings, existence checks etc. > > That'd be great. now, if you could also handle requesting different columns in parallel and processing them out of order. I do. The Parquet file reader api that reads row groups in sync mode reads all columns in sequence. In async mode, it fires off a task for every column blocking only to read the first page of every column before returning. This part also uses a different thread pool from the IO tasks so that IO tasks never wait because there are no available threads in the thread pool. > > be good to think about vectored IO. I think I know how to integrate this PR with the vectored IO, but this is only after a cursory look. > > and yes, updating parquet dependencies would be good, hadoop 3.3.0 should be the baseline. Who can drive this (presumably) non-trivial change? I myself have no karma points :( > just sketched out my thoughts on this. I've played with some of this in my own branch. I think the next step would be for me to look at the benchmark code to make it targetable elsewhere. > > https://docs.google.com/document/d/1y9oOSYbI6fFt547zcQJ0BD8VgvJWdyHBveaiCHzk79k/ This is great. I now have much more context of where you are coming from (and going to) ! > Implement async IO for Parquet file reader > ------------------------------------------ > > Key: PARQUET-2149 > URL: https://issues.apache.org/jira/browse/PARQUET-2149 > Project: Parquet > Issue Type: Improvement > Components: parquet-mr > Reporter: Parth Chandra > Priority: Major > > ParquetFileReader's implementation has the following flow (simplified) - > - For every column -> Read from storage in 8MB blocks -> Read all > uncompressed pages into output queue > - From output queues -> (downstream ) decompression + decoding > This flow is serialized, which means that downstream threads are blocked > until the data has been read. Because a large part of the time spent is > waiting for data from storage, threads are idle and CPU utilization is really > low. > There is no reason why this cannot be made asynchronous _and_ parallel. So > For Column _i_ -> reading one chunk until end, from storage -> intermediate > output queue -> read one uncompressed page until end -> output queue -> > (downstream ) decompression + decoding > Note that this can be made completely self contained in ParquetFileReader and > downstream implementations like Iceberg and Spark will automatically be able > to take advantage without code change as long as the ParquetFileReader apis > are not changed. > In past work with async io [Drill - async page reader > |https://github.com/apache/drill/blob/master/exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/columnreaders/AsyncPageReader.java] > , I have seen 2x-3x improvement in reading speed for Parquet files. -- This message was sent by Atlassian Jira (v8.20.7#820007)