}

    /**
     * Retrieves a list of session IDs with their document counts from the search engine.
     * Uses aggregation to get session segments and their corresponding document counts.
     *
     * @param searchEngineClient the search engine client to perform the query
     * @return a list of maps containing session IDs and their document counts
     */

   *
   * If [routes] is non-null these are the resolved routes (ie. IP addresses) for the connection.
   * This is used to coalesce related domains to the same HTTP/2 connection, such as `square.com`
   * and `square.ca`.
   */
  internal fun callAcquirePooledConnection(
    doExtensiveHealthChecks: Boolean,
    address: Address,
    call: RealCall,
    routes: List<Route>?,
    requireMultiplexed: Boolean,

        assertEquals(0, SMBUtil.readInt2(encoded, 2), "EOL length should be 0");
    }

    /**
     * Test round-trip encoding and decoding
     */
    @Test
    @DisplayName("Round-trip encode and decode should preserve data")
    void testRoundTrip() throws CIFSException {
        List<AvPair> originalPairs = new LinkedList<>();

    return multiset(ImmutableMap.of(value1, count1, value2, count2));
  }

  private static <T> ImmutableMultiset<T> multiset(Map<T, Integer> counts) {
    ImmutableMultiset.Builder<T> builder = ImmutableMultiset.builder();
    for (Entry<T, Integer> entry : counts.entrySet()) {
      builder.addCopies(entry.getKey(), entry.getValue());
    }
    return builder.build();
  }

    return multiset(ImmutableMap.of(value1, count1, value2, count2));
  }

  private static <T> ImmutableMultiset<T> multiset(Map<T, Integer> counts) {
    ImmutableMultiset.Builder<T> builder = ImmutableMultiset.builder();
    for (Entry<T, Integer> entry : counts.entrySet()) {
      builder.addCopies(entry.getKey(), entry.getValue());
    }
    return builder.build();
  }

file: org.apache.spark.rdd.RDD[String] = s3a://testbucket/testdata MapPartitionsRDD[1] at textFile at <console>:24

scala> val counts = file.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)
counts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[4] at reduceByKey at <console>:25

scala> counts.saveAsTextFile("s3a://testbucket/wordcount")
```

Use one of the following approaches to view job output:

# Unteranwendungen – Mounts { #sub-applications-mounts }

Wenn Sie zwei unabhängige FastAPI-Anwendungen mit deren eigenen unabhängigen OpenAPI und deren eigenen Dokumentationsoberflächen benötigen, können Sie eine Hauptanwendung haben und dann eine (oder mehrere) Unteranwendung(en) „mounten“.

## Eine **FastAPI**-Anwendung mounten { #mounting-a-fastapi-application }

# WSGI inkludieren – Flask, Django und andere { #including-wsgi-flask-django-others }

Sie können WSGI-Anwendungen mounten, wie Sie es in [Unteranwendungen – Mounts](sub-applications.md){.internal-link target=_blank}, [Hinter einem Proxy](behind-a-proxy.md){.internal-link target=_blank} gesehen haben.

Dazu können Sie die `WSGIMiddleware` verwenden und damit Ihre WSGI-Anwendung wrappen, zum Beispiel Flask, Django usw.

## `WSGIMiddleware` verwenden { #using-wsgimiddleware }

 * the License.
 */

package com.google.common.hash;

import com.google.common.annotations.GwtIncompatible;
import java.nio.Buffer;

/**
 * Wrappers around {@link Buffer} methods that are covariantly overridden in Java 9+. See
 * https://github.com/google/guava/issues/3990
 */
@GwtIncompatible
final class Java8Compatibility {
  static void clear(Buffer b) {
    b.clear();

  public void remove(Range<K> rangeToRemove) {
    if (rangeToRemove.isEmpty()) {
      return;
    }

    /*
     * The comments for this method will use [ ] to indicate the bounds of rangeToRemove and ( ) to
     * indicate the bounds of ranges in the range map.
     */
    Entry<Cut<K>, RangeMapEntry<K, V>> mapEntryBelowToTruncate =
        entriesByLowerBound.lowerEntry(rangeToRemove.lowerBound);