pkField = db.Statement.Schema.PrioritizedPrimaryField
			pkFieldName = db.Statement.Schema.PrioritizedPrimaryField.DBName
		}

		// append @id column with value for auto-increment primary key
		// the @id value is correct, when: 1. without setting auto-increment primary key, 2. database AutoIncrementIncrement = 1
		switch values := db.Statement.Dest.(type) {
		case map[string]interface{}:
			values[pkFieldName] = insertID

    #
    #; skipSheet = P.+
    # - - - - - - - - - -/

    # /- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    # o isIncrementSequenceToDataMax: (NotRequired - Default false)
    #  Does it increment sequence values to max value of table data?
    #  Referring the property 'sequenceDefinitionMap'.
    #
    #; isIncrementSequenceToDataMax = false
    # - - - - - - - - - -/

    log_id bigint NOT NULL
);

ALTER TABLE public.log_usage ALTER COLUMN log_id ADD GENERATED BY DEFAULT AS IDENTITY (
    SEQUENCE NAME public.log_usage_log_id_seq
    START WITH 1
    INCREMENT BY 1
    NO MINVALUE
    NO MAXVALUE
    CACHE 1
);
	`).Error; err != nil {
		t.Fatalf("failed to create table, got error %v", err)
	}

	columns, err := DB.Migrator().ColumnTypes("log_usage")

      length,
      formattedType,
      formattedFlags,
    )
  }

  /**
   * Returns a human-readable representation of a `WINDOW_UPDATE` frame. This frame includes the
   * window size increment instead of flags.
   */
  fun frameLogWindowUpdate(
    inbound: Boolean,
    streamId: Int,
    length: Int,
    windowSizeIncrement: Long,
  ): String {

    assertEquals(20, ticker.read());

    for (TimeUnit timeUnit : TimeUnit.values()) {
      ticker.setAutoIncrementStep(0, timeUnit);
      assertEquals(
          "Expected no auto-increment when setting autoIncrementStep to 0 " + timeUnit,
          30,
          ticker.read());
    }
  }

  public void testAutoIncrement_negative() {
    FakeTicker ticker = new FakeTicker();

// Input should be root -> object input. Each root indicates a record.
// If r.input is closed, it is assumed that no more input will come.
// When this function returns r.readerWg will be decremented and r.decoded will be closed.
// On errors, r.err will be set. This should only be accessed after r.decoded has been closed.
func (r *Reader) startReader() {
	defer r.onReaderExit()
	var tmpObj simdjson.Object
	for {

		m.expMovingAvg = float64(bytesSinceLastWindow) / duration.Seconds()
		return
	}

	increment := float64(bytesSinceLastWindow) / duration.Seconds()
	m.expMovingAvg = exponentialMovingAverage(beta, m.expMovingAvg, increment)
}

// exponentialMovingAverage calculates the exponential moving average
func exponentialMovingAverage(beta, previousAvg, incrementAvg float64) float64 {

        }

        /* The message provided to batch has a batchLimit that is
         * higher than the current batchLevel so we will now encode
         * that chained message. Before doing so we must increment
         * the batchLevel of the andx message in case it itself is an
         * andx message and needs to perform the same check as above.
         */

        andx.batchLevel = batchLevel + 1;

	startTime := time.Now()
	return func() {
		duration := time.Since(startTime)

		atomic.AddUint64(&o.operations[s], 1)
		o.latency[s].add(duration)
	}
}

// incTime will increment time on metric s with a specific duration.
func (o *osMetrics) incTime(s osMetric, d time.Duration) {
	atomic.AddUint64(&o.operations[s], 1)
	o.latency[s].add(d)
}

 * the response, the client will issue a conditional `GET`. The server will then send either
 * the updated response if it has changed, or a short 'not modified' response if the client's copy
 * is still valid. Such responses increment both the network count and hit count.
 *
 * The best way to improve the cache hit rate is by configuring the web server to return cacheable