wgtmac commented on code in PR #3726:
URL: https://github.com/apache/parquet-java/pull/3726#discussion_r4089442748
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parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java:
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@@ -1358,32 +1355,150 @@ private boolean
arePartsValidForVectoredIo(List<ConsecutivePartList> allParts) {
* If directly implemented by a Filesystem then it is likely to be a more
efficient
* operation such as a scatter-gather read (native IO) or set of parallel
* GET requests against an object store.
+ * Submission and all requested ranges share the vectored-read timeout.
Failed
+ * operations invalidate the stream; cleanup waits for submission to exit
before
+ * closing it, even if the backend does not respond promptly to interruption.
+ * The allocation limit bounds requested range lengths. Filesystems may
merge or
+ * checksum-align ranges and allocate larger buffers; decoders may also
require
+ * larger contiguous buffers. This is not a total memory limit.
* @param allParts all parts to be read.
* @param builder used to build chunk list to read the pages for the
different columns.
- * @throws IOException any IOE.
- * @throws IllegalArgumentException arguments are invalid.
- * @throws UnsupportedOperationException if the filesystem does not support
vectored IO.
+ * @throws IOException if submitting or consuming the vectored reads fails.
+ * @throws IllegalArgumentException if range preparation fails before any
reads are submitted.
*/
private void readVectored(List<ConsecutivePartList> allParts,
ChunkListBuilder builder) throws IOException {
-
+ final int maximumAllocation = options.getMaxAllocationSize();
+ Preconditions.checkArgument(maximumAllocation > 0, "Invalid maximum
allocation size %s", maximumAllocation);
+ final long fileLength = vectoredReadFileLength;
List<ParquetFileRange> ranges = new ArrayList<>(allParts.size());
+ List<Integer> partRangeCounts = new ArrayList<>(allParts.size());
long totalSize = 0;
for (ConsecutivePartList consecutiveChunks : allParts) {
final long len = consecutiveChunks.length;
- Preconditions.checkArgument(
- len < Integer.MAX_VALUE,
- "Invalid length %s for vectored read operation. It must be less than
max integer value.",
- len);
- ranges.add(new ParquetFileRange(consecutiveChunks.offset, (int) len));
+ final long start = consecutiveChunks.offset;
+ if (start < 0 || len < 0 || start > fileLength || len > fileLength -
start) {
+ throw new IOException(String.format(
+ "Invalid vectored read range (offset %d, length %d) for file
length %d",
+ start, len, fileLength));
+ }
+ final int firstRange = ranges.size();
+ long remaining = len;
+ long offset = start;
+ do {
+ int rangeLength = (int) Math.min(remaining, maximumAllocation);
+ ranges.add(new ParquetFileRange(offset, rangeLength));
+ offset += rangeLength;
+ remaining -= rangeLength;
+ } while (remaining > 0);
+ partRangeCounts.add(ranges.size() - firstRange);
totalSize += len;
}
LOG.debug("Reading {} bytes of data with vectored IO in {} ranges",
totalSize, ranges.size());
- // Request a vectored read;
- f.readVectored(ranges, options.getAllocator());
- int k = 0;
- for (ConsecutivePartList consecutivePart : allParts) {
- ParquetFileRange currRange = ranges.get(k++);
- consecutivePart.readFromVectoredRange(currRange, builder);
+ if (vectoredReadExecutor == null) {
+ vectoredReadExecutor = VectoredReadOperation.newExecutor();
Review Comment:
A blocked backend call still uses one worker per reader with no global
bound. Is this acceptable for workloads with many concurrent readers?
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