assertThat(IDNA_MAPPING_TABLE.mappings).isEqualTo(compactTable.mappings)
  }

  private fun String.map(): String {
    val buffer = Buffer()
    for (codePoint in codePoints()) {
      require(table.map(codePoint, buffer))
    }
    return buffer.readUtf8()
  }

  private fun String.mapExpectingErrors(): String {
    val buffer = Buffer()
    var errorCount = 0

workloads typically interact with object stores in the same way they do with HDFS. These workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. _Netflix_, for example, developed two new staging committers...

Client [Quickstart Guide](https://min.io/docs/minio/linux/reference/minio-mc.html#quickstart) for further instructions. ## Upgrading MinIO Upgrades require zero downtime in MinIO, all upgrades are non-disruptive, all transactions on MinIO are atomic. So upgrading all the servers simultaneously is the recommended way to upgrade MinIO. > NOTE: requires internet access to update directly from <https://dl.min.io>, optionally you can host any mirrors at <https://my-artifactory.example.com/minio/> - For...

			return
		}
	}
	return
}

// MarshalMsg implements msgp.Marshaler
func (z *allTierStats) MarshalMsg(b []byte) (o []byte, err error) {
	o = msgp.Require(b, z.Msgsize())
	// map header, size 1
	// string "ts"
	o = append(o, 0x81, 0xa2, 0x74, 0x73)
	o = msgp.AppendMapHeader(o, uint32(len(z.Tiers)))
	for za0001, za0002 := range z.Tiers {

        when {
          it.sourceCodePoint1 < codePoint -> -1
          it.sourceCodePoint0 > codePoint -> 1
          else -> 0
        }
      }

    // Code points must be in 0..0x10ffff.
    require(index in mappings.indices) { "unexpected code point: $codePoint" }

    val mapping = mappings[index]
    var result = true

    when (mapping.type) {
      TYPE_IGNORED -> Unit

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.
* **Computer vision**: an image is composed of millions of pixels, each pixel has 3 values / colors, processing that normally requires computing something on those pixels, all at the same time.

		if err != nil {
			err = msgp.WrapError(err, zb0003)
			return
		}
	}
	return
}

// MarshalMsg implements msgp.Marshaler
func (z BatchJobPrefix) MarshalMsg(b []byte) (o []byte, err error) {
	o = msgp.Require(b, z.Msgsize())
	o = msgp.AppendArrayHeader(o, uint32(len(z)))
	for zb0003 := range z {
		o = msgp.AppendString(o, z[zb0003])
	}
	return
}

// UnmarshalMsg implements msgp.Unmarshaler

   *
   * @deprecated Use {@code table.rowKeySet().comparator()} instead.
   */
  @Deprecated
  public Comparator<? super R> rowComparator() {
    /*
     * requireNonNull is safe because the factories require non-null Comparators, which they pass on
     * to the backing collections.
     */
    return requireNonNull(rowKeySet().comparator());
  }

  /**

and can heal one object at a time. For RAID, healing can be done only at the volume level which translates into high downtime. As MinIO encodes each object individually, it can heal objects incrementally. Storage servers once deployed should not require drive replacement or healing for the lifetime of the server. MinIO's erasure coded backend is designed for operational efficiency and takes full advantage of hardware acceleration whenever available.

![Erasure](https://github.com/minio/m...

 *  @author Victor Jonsson, http://victorjonsson.se
 *  @license MIT
 */