Random r = new Random(9);
    for (int i = 0; i < ITERS; i++) {
      countRemaps(r.nextLong(), map);
    }
    for (int shard = 2; shard <= MAX_SHARDS; shard++) {
      // Rough: don't exceed 1.2x the expected number of remaps by more than 20
      assertThat((double) map.get(shard)).isAtMost(1.2 * ITERS / shard + 20);
    }
  }

  private void countRemaps(long h, AtomicLongMap<Integer> map) {
    int last = 0;

									}
									// Update to new config and add current
									valid := 0
									for shardIdx, shard := range splitFilled[:k] {
										shardConfig[shardIdx] = shard[offset]
										valid += int(shard[offset])
										if shard[offset] == 0 {
											shards[shardIdx] = shards[shardIdx][:0]
										} else {

	StandardEnv = "MINIO_STORAGE_CLASS_STANDARD"
	// Optimize storage class environment variable
	OptimizeEnv = "MINIO_STORAGE_CLASS_OPTIMIZE"
	// Inline block indicates the size of the shard
	// that is considered for inlining, remember this
	// shard value is the value per drive shard it
	// will vary based on the parity that is configured
	// for the STANDARD storage_class.
	// inlining means data and metadata are written

                current.println("        body: |")
                body.eachLine { current.println("          $it") }
            }
            /* Catch any shard failures. These only cause a non-200 response if
             * no shard succeeds. But we need to fail the tests on all of these
             * because they mean invalid syntax or broken queries or something

          required: false
          schema:
            type: string
            example: en
        - name: preference
          in: query
          description: String to specify a shard for searching
          required: false
          schema:
            type: string
            example: abc
        - name: callback
          in: query
          description: Callback name for using JSONP

	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as
	// pick 10 nodes that precisely can send those 100 requests the first node
	// in the 10 node shard would coordinate between other 9 shards to get the
	// rest of the `99*9` requests.
	//

			disks := er.getDisks()
			distribution := hashOrder(pathJoin(bucket, object), nDisks)
			shuffledDisks := shuffleDisks(disks, distribution)

			// remove last data shard
			err = removeAll(pathJoin(shuffledDisks[11].String(), bucket, object))
			if err != nil {
				t.Fatalf("Failed to delete a file - %v", err)
			}
			_, err = obj.HealObject(ctx, bucket, object, "", madmin.HealOpts{

==== Refactor code to make it easier to test

Unfortunately, a large part of our code base is still hard to unit test.
Sometimes because some classes have lots of dependencies that make them hard to
instantiate. Sometimes because API contracts make tests hard to write. Code
refactors that make functionality easier to unit test are encouraged. If this
sounds very abstract to you, you can have a look at

            return;
        case 2:
            hard = true;
        case 3: /* connected - go ahead and disconnect */
            if (response_map.size() != 0 && !hard) {
                break; /* outstanding requests */
            }
            try {
                doDisconnect(hard);
            } catch (final IOException ioe0) {
                ioe = ioe0;
            }

    /**
     * Disconnect the transport
     *
     * @param hard if true, disconnect immediately without waiting for outstanding requests
     * @return whether connection was in use
     * @throws IOException if an I/O error occurs during disconnection
     */
    public synchronized boolean disconnect(final boolean hard) throws IOException {
        return disconnect(hard, true);
    }

    /**
     * Disconnect the transport