*
 * <p>This implementation is based on the <a
 * href="http://portal.acm.org/citation.cfm?id=6621">min-max heap</a> developed by Atkinson, et al.
 * Unlike many other double-ended priority queues, it stores elements in a single array, as compact
 * as the traditional heap data structure used in {@link PriorityQueue}.
 *
 * <p>This class is not thread-safe, and does not accept null elements.
 *
 * <p><i>Performance notes:</i>
 *
 * <ul>

* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

  After the connection closed(received GOAWAY), the client's other in-flight requests won't be affected, and the client will reconnect. 
  The flag min value is 0 (off), max is .02 (1/50 requests); .001 (1/1000) is a recommended starting point.

    val response = call.execute()
    assertThat(response.body.string()).isEqualTo("ABC")
    assertThat(response.protocol).isEqualTo(protocol)

    // Confirm a single ping was sent and received, and its reply was sent and received.
    val logs = testLogHandler.takeAll()
    assertThat(countFrames(logs, "FINE: >> 0x00000000     8 PING          "))
      .isEqualTo(1)

			t.Errorf("want %q, got %q", testPayload, string(resp))
		}
		t.Log("Roundtrip:", time.Since(start))
	})

	t.Run("localToRemoteErr", func(t *testing.T) {
		const testPayload = "Hello Grid World!"
		start := time.Now()
		resp, err := remoteConn.Request(t.Context(), handlerTest2, []byte(testPayload))
		t.Log("Roundtrip:", time.Since(start))
		if len(resp) != 0 {
			t.Errorf("want nil, got %q", string(resp))
		}

	}

	currentLogger.Trace(tx.Statement.Context, newLogger.BeginAt, func() (string, int64) {
		return newLogger.SQL, tx.RowsAffected
	}, tx.Error)
	tx.Logger = currentLogger
	return
}

// Pluck queries a single column from a model, returning in the slice dest. E.g.:
//
//	var ages []int64
//	db.Model(&users).Pluck("age", &ages)
func (db *DB) Pluck(column string, dest interface{}) (tx *DB) {
	tx = db.getInstance()

			yBytes := Repeat(y, growLen)
			allocs := testing.AllocsPerRun(100, func() {
				buf.Grow(growLen)
				buf.Write(yBytes)
			})
			// Check no allocation occurs in write, as long as we're single-threaded.
			if allocs != 0 {
				t.Errorf("allocation occurred during write")
			}
			// Check that buffer has correct data.
			if !Equal(buf.Bytes()[0:startLen-readBytes], xBytes[readBytes:]) {

    - [Node Binaries](#node-binaries)
  - [Changelog since v1.10.12](#changelog-since-v11012)
    - [Other notable changes](#other-notable-changes)
- [v1.10.12](#v11012)
  - [Downloads for v1.10.12](#downloads-for-v11012)
    - [Client Binaries](#client-binaries-1)
    - [Server Binaries](#server-binaries-1)
    - [Node Binaries](#node-binaries-1)
  - [Changelog since v1.10.11](#changelog-since-v11011)

   * optimized to saved memory. Since {@link MapMaker.Dummy} is a singleton, we don't need to store
   * any values at all. Because of this optimization, {@code build.getValueStrength()} must be
   * {@link Strength#STRONG}.
   *
   * <p>This method is intended to only be used by the internal implementation of {@link Interners},
   * since a map of dummy values is the exact use case there.
   */
  static <K>

                .collect(Collectors.toMap(
                        upgrade -> upgrade.groupId() + ":" + upgrade.artifactId(), upgrade -> upgrade));
    }

    /**
     * Analyzes the effective model for a single POM to find plugins that need upgrades.
     */
    private Set<String> analyzeEffectiveModelForPlugins(
            UpgradeContext context, Path tempPomPath, Map<String, PluginUpgrade> pluginUpgrades) {