LinkedList(subProjectTestClassTimes),
            SubprojectTestClassTime::totalTime,
            { largeElement, factor ->
                List(factor) { SmallSubprojectBucket(largeElement.subProject, parallelization(factor)) }
            },
            { list ->
                SmallSubprojectBucket(list.map { it.subProject }, parallelization(1))
            },

  private static final double DESIRED_LOAD_FACTOR = 0.5;

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing
   * with linear probing in its implementation. The returned size is the smallest power of two that
   * can hold setSize elements with the desired load factor.
   */
  @VisibleForTesting
  static int chooseTableSize(int setSize) {

  static final int DEFAULT_EDGE_COUNT = DEFAULT_NODE_COUNT * EXPECTED_DEGREE;

  // Load factor and capacity for "inner" (i.e. per node/edge element) hash sets or maps
  static final float INNER_LOAD_FACTOR = 1.0f;
  static final int INNER_CAPACITY = 2; // ceiling(EXPECTED_DEGREE / INNER_LOAD_FACTOR)

  // Error messages
  static final String NODE_NOT_IN_GRAPH = "Node %s is not an element of this graph.";

          sink.writeUtf8("-------\n")
          for (i in 2..997) {
            sink.writeUtf8(String.format(" * $i = ${factor(i)}\n"))
          }
        }

        private fun factor(n: Int): String {
          for (i in 2 until n) {
            val x = n / i
            if (x * i == n) return "${factor(x)} × $i"
          }
          return n.toString()
        }
      }

    val request =
      Request(

  private static final double DESIRED_LOAD_FACTOR = 0.5;

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing
   * with linear probing in its implementation. The returned size is the smallest power of two that
   * can hold setSize elements with the desired load factor.
   */
  @VisibleForTesting
  static int chooseTableSize(int setSize) {

     */
    protected static final float DEFAULT_LOAD_FACTOR = 0.75f;

    /**
     * 上限サイズです。
     */
    protected final int limitSize;

    /**
     * {@link LruHashMap}を作成します。
     *
     * @param limitSize
     *            エントリ数の上限
     */
    public LruHashMap(final int limitSize) {
        this(limitSize, DEFAULT_INITIAL_CAPACITY, DEFAULT_LOAD_FACTOR);
    }

    /**
     * {@link LruHashMap}を作成します。

# use single binary and filesystem storage for test
# do not use in production
loki:
  useTestSchema: true
  auth_enabled: false
  commonConfig:
    replication_factor: 1
  storage:
    type: 'filesystem'
test:
  enabled: false
lokiCanary:
  enabled: false
monitoring:
  dashboards:
    enabled: false
  rules:
    enabled: false
    alerting: false
  serviceMonitor:
    enabled: false
    metricsInstance:

  // Might also explore collocating all of [hash, next, predecessor, successor] fields of an
  // entry in a *single* long[], though that reduces the maximum size of the set by a factor of 2

  /**
   * Pointer to the predecessor of an entry in insertion order. ENDPOINT indicates a node is the
   * first node in insertion order; all values at indices ≥ {@link #size()} are UNSET.
   */

    implements ClassToInstanceMap<B>, Serializable {

  /**
   * Returns a new {@code MutableClassToInstanceMap} instance backed by a {@link HashMap} using the
   * default initial capacity and load factor.
   */
  public static <B extends @Nullable Object> MutableClassToInstanceMap<B> create() {
    return new MutableClassToInstanceMap<>(new HashMap<Class<? extends @NonNull B>, B>());
  }

  /**

- Already compressed objects are not fit for compression since they do not have compressible patterns.
Such objects do not produce efficient [`LZ compression`](https://en.wikipedia.org/wiki/LZ77_and_LZ78)
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.