"hash"
	"io"
)

// Implementation to calculate bitrot for the whole file.
type wholeBitrotWriter struct {
	disk      StorageAPI
	volume    string
	filePath  string
	shardSize int64 // This is the shard size of the erasure logic
	hash.Hash       // For bitrot hash
}

func (b *wholeBitrotWriter) Write(p []byte) (int, error) {
	err := b.disk.AppendFile(context.TODO(), b.volume, b.filePath, p)
	if err != nil {

			if test.reconstructParity {
				for j := range decoded {
					if decoded[j] == nil {
						t.Errorf("Test %d: failed to reconstruct shard %d", i, j)
					}
				}
			} else {
				for j := range decoded[:test.dataBlocks] {
					if decoded[j] == nil {
						t.Errorf("Test %d: failed to reconstruct data shard %d", i, j)
					}
				}
			}

			decodedData := new(bytes.Buffer)

    /**
     * Gets the number of shards for the queue index.
     *
     * @return the number of queue shards
     */
    @Override
    public int getQueueShards() {
        return ComponentUtil.getFessConfig().getIndexDocumentCrawlerQueueNumberOfShardsAsInteger();
    }

    /**
     * Gets the number of shards for the data index.
     *
     * @return the number of data shards
     */
    @Override

				fmt.Fprintf(os.Stderr, "%v: error on self-test [d:%d,p:%d]: want %#v, got %#v\n", algo, conf[0], conf[1], a, b)
				ok = false
				continue
			}
			// Delete first shard and reconstruct...
			first := encoded[0]
			encoded[0] = nil
			failOnErr(e.DecodeDataBlocks(encoded))
			if a, b := first, encoded[0]; !bytes.Equal(a, b) {

				// Reading first time on this disk, hence the buffer needs to be allocated.
				// Subsequent reads will reuse this buffer.
				p.buf[bufIdx] = make([]byte, p.shardSize)
			}
			// For the last shard, the shardsize might be less than previous shard sizes.
			// Hence the following statement ensures that the buffer size is reset to the right size.
			p.buf[bufIdx] = p.buf[bufIdx][:p.shardSize]
			n, err := rr.ReadAt(p.buf[bufIdx], p.offset)

code is a mathematical algorithm to reconstruct missing or corrupted data. MinIO uses Reed-Solomon code to shard objects into variable data and parity blocks. For example, in a 12 drive setup, an object can be sharded to a variable number of data and parity blocks across all the drives - ranging from six data and six parity blocks to ten data and two parity blocks.

By default, MinIO shards the objects across N/2 data and N/2 parity drives. Though, you can use [storage classes](https://github...

    public String getWriteableName() {
        return queryBuilder.getWriteableName();
    }

    /**
     * Creates a Lucene Query from this query builder.
     *
     * @param context the query shard context
     * @return the Lucene Query
     * @throws IOException if an I/O error occurs
     */
    @Override
    public Query toQuery(final QueryShardContext context) throws IOException {

- Erasure coding used by MinIO is [Reed-Solomon](https://github.com/klauspost/reedsolomon) erasure coding scheme, which has a total shard maximum of 256 i.e 128 data and 128 parity. MinIO design goes beyond this limitation by doing some practical architecture choices.

    /**
     * Constructs a tree connect AndX request to establish a connection to a shared resource.
     *
     * @param ctx the CIFS context containing configuration
     * @param server the server data containing security information
     * @param path the UNC path to the shared resource
     * @param service the service type (e.g., "A:" for disk share, "LPT1:" for printer)
     * @param andx the next command in the AndX chain, or null
     */

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