return carpWithPayload(carpPayload)
			}(),
		},
		{
			name: "an obj with 10kB payload",
			obj: func() runtime.Object {
				carpPayload := make([]byte, 10000) // 10 kB
				if _, err := rand.Read(carpPayload); err != nil {
					panic(err)
				}
				return carpWithPayload(carpPayload)
			}(),
		},
		{
			name: "an obj with 100kB payload",
			obj: func() runtime.Object {

## Troubleshooting

In Kubernetes clusters in version 1.10.0 or later, fluentd-gcp DaemonSet can be
manually scaled. This is useful e.g. when applications running in the cluster
are sending a large volume of logs (i.e. over 100kB/s), causing fluentd-gcp to
fail with OutOfMemory errors. Conversely, if the applications aren't generating
a lot of logs, it may be useful to reduce the amount of resources consumed by

			s3Select.Close()
		}
	})
}

func benchmarkSelectAll(b *testing.B, count int) {
	benchmarkSelect(b, count, "select * from S3Object")
}

// BenchmarkSelectAll_100K - benchmark * function with 100k records.
func BenchmarkSelectAll_100K(b *testing.B) {
	benchmarkSelectAll(b, 100*humanize.KiByte)
}

// BenchmarkSelectAll_1M - benchmark * function with 1m records.
func BenchmarkSelectAll_1M(b *testing.B) {

    features {
        freeDiskSpace {
            // Lower the limit such that the agent work directories aren't cleaned during the AMI baking process
            requiredSpace = "100mb"
        }
    }

    params {
        param("defaultBranchName", "master")
        param("env.JAVA_HOME", javaHome(BuildToolBuildJvm, Os.LINUX))
    }

    steps {
        gradleWrapper {

# Vars assumed:
#   NUM_NODES
#   NUM_WINDOWS_NODES
function get-master-root-disk-size() {
  local suggested_master_root_disk_size="20GB"
  if [[ "$(get-num-nodes)" -gt "500" ]]; then
    suggested_master_root_disk_size="100GB"
  fi
  if [[ "$(get-num-nodes)" -gt "3000" ]]; then
    suggested_master_root_disk_size="500GB"
  fi
  echo "${suggested_master_root_disk_size}"
}

# Vars assumed:
#   NUM_NODES
#   NUM_WINDOWS_NODES

	"k8s.io/kubernetes/pkg/features"
	"k8s.io/kubernetes/pkg/kubelet/util/ioutils"
	"k8s.io/kubernetes/pkg/probe"

	"k8s.io/klog/v2"
	"k8s.io/utils/exec"
)

const (
	maxReadLength = 10 * 1 << 10 // 10KB
)

// New creates a Prober.
func New() Prober {
	return execProber{}
}

// Prober is an interface defining the Probe object for container readiness/liveness checks.
type Prober interface {

			expectValue: trueVal,
		},
		{
			name:        "arith_chain_1",
			expr:        `quantity("50k").add(20).sub(quantity("100k")).asInteger()`,
			expectValue: types.Int(-49980),
		},
		{
			name:        "arith_chain",
			expr:        `quantity("50k").add(20).sub(quantity("100k")).sub(-50000).asInteger()`,
			expectValue: types.Int(20),
		},
		{
			name:        "as_integer",

        assertEquals("1.024KB", MemoryUtil.byteCountToDisplaySize(FileUtils.ONE_KB));
        assertEquals("999.999KB", MemoryUtil.byteCountToDisplaySize(999_999L));
        assertEquals("1000KB", MemoryUtil.byteCountToDisplaySize(1000_000L));
        assertEquals("1.024MB", MemoryUtil.byteCountToDisplaySize(FileUtils.ONE_MB));
        assertEquals("976.562MB", MemoryUtil.byteCountToDisplaySize(999_999_999L));

- This API behavior is limited for following **read** operations on files inside a zip archive:
  - `HeadObject`
  - `GetObject`
  - `ListObjectsV2`
- If the ZIP file directory isn't located within the last 100MB the file will not be parsed.
- A maximum of 100M inside a single zip is allowed. However, a reasonable limit of 100,000 files inside a single ZIP archive is recommended for best performance and memory usage trade-off.

## Content-Type

  # Pod resource configuration
  resources:
    requests:
      cpu: 200m
      # Ztunnel memory scales with the size of the cluster and traffic load
      # While there are many factors, this is enough for ~200k pod cluster or 100k concurrently open connections.
      memory: 512Mi

  # List of secret names to add to the service account as image pull secrets
  imagePullSecrets: []

  # A `key: value` mapping of environment variables to add to the pod