// Represents how tightly we can pack things, as a maximum.
  private static final double DESIRED_LOAD_FACTOR = 0.7;

  // If the set has this many elements, it will "max out" the table size
  private static final int CUTOFF = (int) (MAX_TABLE_SIZE * DESIRED_LOAD_FACTOR);

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing

          command: [
            "/bin/sh",
            "-ce",

# 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:

  // Represents how tightly we can pack things, as a maximum.
  private static final double DESIRED_LOAD_FACTOR = 0.7;

  // If the set has this many elements, it will "max out" the table size
  private static final int CUTOFF = (int) (MAX_TABLE_SIZE * DESIRED_LOAD_FACTOR);

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing

import static com.google.common.base.Preconditions.checkState;
import static com.google.common.graph.GraphConstants.INNER_CAPACITY;
import static com.google.common.graph.GraphConstants.INNER_LOAD_FACTOR;
import static com.google.common.graph.Graphs.checkNonNegative;
import static com.google.common.graph.Graphs.checkPositive;

import com.google.common.base.Function;
import com.google.common.collect.AbstractIterator;

    }
  }

  private static final int DEFAULT_KEY_CAPACITY = 16;
  private static final int DEFAULT_VALUE_SET_CAPACITY = 2;
  @VisibleForTesting static final double VALUE_SET_LOAD_FACTOR = 1.0;

  @VisibleForTesting transient int valueSetCapacity = DEFAULT_VALUE_SET_CAPACITY;
  private transient ValueEntry<K, V> multimapHeaderEntry;

  private LinkedHashMultimap(int keyCapacity, int valueSetCapacity) {

  // 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.
   */

        Serialization.getFieldSetter(ConcurrentHashMultiset.class, "countMap");
  }

  /**
   * Creates a new, empty {@code ConcurrentHashMultiset} using the default initial capacity, load
   * factor, and concurrency settings.
   */
  public static <E> ConcurrentHashMultiset<E> create() {
    // TODO(schmoe): provide a way to use this class with other (possibly arbitrary)

    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.