speak = math.Max(math.Max(v[Small].Peak, speak), v[Small].Curr)
		if lpeak > 0 || speak > 0 {
			count++
		}
	}
	if count > 0 {
		lrg := XferStats{
			Avg:  lavg / float64(count),
			Curr: lcurr / float64(count),
			Peak: lpeak,
		}
		sml := XferStats{
			Avg:  savg / float64(count),
			Curr: scurr / float64(count),
			Peak: speak,
		}
		qs.XferStats[Large] = lrg
		qs.XferStats[Small] = sml

And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.

### Server Memory { #server-memory }

	}

	allErrs := make([]error, 0, len(objsToDel))

	for {
		count := len(objsToDel)
		if count == 0 {
			break
		}
		if count > maxDeleteList {
			count = maxDeleteList
		}
		_, errs := api.DeleteObjects(ctx, r.Bucket, objsToDel[:count], opts)
		allErrs = append(allErrs, errs...)
		// Next batch of deletion
		objsToDel = objsToDel[count:]
	}

	return allErrs
}

const (

you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

And then you can set those same memory limits and requirements in your configurations for your container management system (for example in **Kubernetes**). That way it will be able to **replicate the containers** in the **available machines** taking into account the amount of memory needed by them, and the amount available in the machines...

		tok := p.next()
		ext = tok.String()
	}
	if p.peek() == lex.LSH {
		// parses left shift amount applied after extension: <<Amount
		p.get(lex.LSH)
		tok := p.get(scanner.Int)
		amount, err := strconv.ParseInt(tok.String(), 10, 16)
		if err != nil {
			p.errorf("parsing left shift amount: %s", err)
		}
		num = int16(amount)
	} else if p.peek() == '[' {
		// parses an element: [Index]
		p.get('[')

	}
}

// getScannedItemsCount - returns a count of all scanned items
func (h *healSequence) getScannedItemsCount() int64 {
	var count int64
	h.mutex.RLock()
	defer h.mutex.RUnlock()

	for _, v := range h.scannedItemsMap {
		count += v
	}
	return count
}

// getScannedItemsMap - returns map of all scanned items against type

	for _, u := range batch {
		if u.ID == 0 {
			t.Fatalf("no primary key found for %v", u)
		}
	}

	count, err := gorm.G[User](DB).Where("name like ?", "GenericsCreateInBatches%").Count(ctx, "*")
	if err != nil {
		t.Fatalf("Count failed: %v", err)
	}
	if count != 3 {
		t.Errorf("expected 3 records, got %d", count)
	}

            final byte[] buf = buffer.array();
            int len;
            int amount = 0;
            while ((len = ChannelUtil.read(channel, buffer, amount)) != -1) {
                out.write(buf, 0, len);
                buffer.clear();
                amount += len;
            }
            out.flush();
            return amount;
        } catch (final IOException e) {
            throw new IORuntimeException(e);

  // Java 9. This function is just returns the same result that
  // Arrays.equals(array1, 0, count, array2, 0, count) would. It assumes that both arrays have a
  // length of at least count.
  private static boolean arraysEqual(byte[] array1, byte[] array2, int count) {
    for (int i = 0; i < count; i++) {
      if (array1[i] != array2[i]) {
        return false;
      }
    }
    return true;
  }

type EndpointServerPools []PoolEndpoints

// ESCount returns the total number of erasure sets in this cluster
func (l EndpointServerPools) ESCount() (count int) {
	for _, p := range l {
		count += p.SetCount
	}
	return count
}

// GetNodes returns a sorted list of nodes in this cluster
func (l EndpointServerPools) GetNodes() (nodes []Node) {
	nodesMap := make(map[string]Node)