if meta.Deleted || meta.IsRemote() {
			continue
		}

		// Always check data, if we got it.
		if (len(meta.Data) > 0 || meta.Size == 0) && len(meta.Parts) > 0 {
			checksumInfo := meta.Erasure.GetChecksumInfo(meta.Parts[0].Number)
			verifyErr := bitrotVerify(bytes.NewReader(meta.Data),
				int64(len(meta.Data)),
				meta.Erasure.ShardFileSize(meta.Size),
				checksumInfo.Algorithm,

public class AvTargetName extends AvPair {

    /**
     *
     */
    private static final Charset UTF16LE = StandardCharsets.UTF_16LE;

    /**
     * Constructs an AvTargetName from raw byte data
     *
     * @param raw the raw byte data for the target name AV pair
     */
    public AvTargetName(final byte[] raw) {
        super(AvPair.MsvAvTargetName, raw);
    }

    /**

## Use case { #use-case }

For example, imagine that you want to return an HTTP status code of "OK" `200` by default.

But if the data didn't exist, you want to create it, and return an HTTP status code of "CREATED" `201`.

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter { #use-a-response-parameter }

// migration fails upon any error.
func formatErasureMigrateV1ToV2(data []byte, version string) ([]byte, error) {
	if version != formatErasureVersionV1 {
		return nil, fmt.Errorf(`format version expected %s, found %s`, formatErasureVersionV1, version)
	}

	formatV1 := &formatErasureV1{}
	if err := json.Unmarshal(data, formatV1); err != nil {
		return nil, err
	}

	formatV2 := &formatErasureV2{}

## Why distributed MinIO?

MinIO in distributed mode can help you setup a highly-available storage system with a single object storage deployment. With distributed MinIO, you can optimally use storage devices, irrespective of their location in a network.

### Data protection

# Maximum document cache size for data in the indexer.
indexer.data.max.document.cache.size=10000
# Maximum document request size (bytes) for data in the indexer.
indexer.data.max.document.request.size=1048576
# Maximum delete cache size for data in the indexer.
indexer.data.max.delete.cache.size=100
# Maximum redirect count for data in the indexer.
indexer.data.max.redirect.count=10

        assertTrue(response.hasMoreElements());
    }

    @Test
    @DisplayName("Test data handling with various sizes")
    void testDataHandlingWithVariousSizes() {
        // Test with small data count
        response.setDataCount(10);
        assertEquals(10, response.getDataCount());

        // Test with large data count
        response.setDataCount(65535);
        assertEquals(65535, response.getDataCount());

				href="#searchOptions" class="badge text-bg-primary text-decoration-none"
				data-bs-toggle="collapse"> <la:message
						key="labels.searchoptions_num" arg0="${f:h(num)}" />
			</a></li>
			<li class="list-inline-item"><la:message key="labels.searchoptions_menu_lang" /> <a
				href="#searchOptions" class="badge text-bg-primary text-decoration-none"
				data-bs-toggle="collapse"> <c:if test="${empty lang}">

				href="#searchOptions" class="badge text-bg-primary text-decoration-none"
				data-bs-toggle="collapse"> <la:message
						key="labels.searchoptions_num" arg0="${f:h(num)}" />
			</a></li>
			<li class="list-inline-item"><la:message key="labels.searchoptions_menu_lang" /> <a
				href="#searchOptions" class="badge text-bg-primary text-decoration-none"
				data-bs-toggle="collapse"> <c:if test="${empty lang}">

which is a fitness factor for a lossless data compression.

Pre-compressed input typically compresses in excess of 2GiB/s per core,
so performance impact should be minimal even if precompressed data is re-compressed.
Decompressing incompressible data has no significant performance impact.