Hi all,
In spark 2.2.1, when I load parquet files, it shows differently ordered
result of original dataset.
It seems like FileSourceScanExec.createNonBucketedReadRDD method sorts
parquet file splits by their own lengths.
-------------
val splitFiles = selectedPartitions.flatMap { partition =>
partition.files.flatMap { file =>
val blockLocations = getBlockLocations(file)
if (fsRelation.fileFormat.isSplitable(
fsRelation.sparkSession, fsRelation.options, file.getPath)) {
(0L until file.getLen by maxSplitBytes).map { offset =>
val remaining = file.getLen - offset
val size = if (remaining > maxSplitBytes) maxSplitBytes else
remaining
val hosts = getBlockHosts(blockLocations, offset, size)
PartitionedFile(
partition.values, file.getPath.toUri.toString, offset, size,
hosts)
}
} else {
val hosts = getBlockHosts(blockLocations, 0, file.getLen)
Seq(PartitionedFile(
partition.values, file.getPath.toUri.toString, 0, file.getLen,
hosts))
}
}
}*.toArray.sortBy(_.length)(implicitly[Ordering[Long]].reverse)*
----------------
So the partitions representing the part-xxxxx.parquet files are always
shuffled when I load them.
How can I preserve the order of a original data?
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