if (i != 0) {
		fprintf(stderr, "pthread_kill: %s\n", strerror(i));
		exit(EXIT_FAILURE);
	}

	// Wait until the signal has been delivered.
	i = 0;
	while (SIGIOCount() == 0) {
		ts.tv_sec = 0;
		ts.tv_nsec = 1000000;
		nanosleep(&ts, NULL);
		i++;
		if (i > 5000) {
			fprintf(stderr, "looping too long waiting for signal\n");
			exit(EXIT_FAILURE);
		}
	}

	// We should still be on the same signal stack.

  fun largeRead() {
    val data = randomByteString(1000000)
    write(data)
    val operator =
      FileOperator(
        randomAccessFile!!.getChannel(),
      )
    val buffer = Buffer()
    operator.read(0, buffer, data.size.toLong())
    assertThat(buffer.readByteString()).isEqualTo(data)
  }

  @Test
  fun largeWrite() {
    val data = randomByteString(1000000)
    val operator =
      FileOperator(

    }

    def "equals impl"() {
        expect:
        key("AAAAAAAA") == key(2863311530)
    }

    def "comparison"() {
        expect:
        key("00000000") < key("00000001")
        key("00000001") > key("00000000")
    }

logging:
  flushFrequency: 5s
  format: text
  options:
    json:
      infoBufferSize: "0"
    text:
      infoBufferSize: "0"
  verbosity: 0
makeIPTablesUtilChains: true
maxOpenFiles: 1000000
maxPods: 110
memoryManagerPolicy: None
memorySwap: {}
memoryThrottlingFactor: 0.9
nodeLeaseDurationSeconds: 40
nodeStatusMaxImages: 50
nodeStatusReportFrequency: 5m0s
nodeStatusUpdateFrequency: 10s

package org.gradle.test.fixtures.concurrent

class Duration {
    private final long nanos

    Duration(long nanos) {
        this.nanos = nanos
    }

    long getMillis() {
        return nanos / 1000000
    }

    @Override
    String toString() {
        return "[$nanos nanos]"
    }

app = Flask(__name__)


@app.route('/hello')
def hello():
    version = os.environ.get('SERVICE_VERSION')

    # do some cpu intensive computation
    x = 0.0001
    for i in range(0, 1000000):
        x = x + math.sqrt(x)

    return 'Hello version: %s, instance: %s\n' % (version, os.environ.get('HOSTNAME'))


@app.route('/health')
def health():
    return 'Helloworld is healthy', 200

  }

  public void testAutoIncrementStep_millis() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(1, TimeUnit.MILLISECONDS);
    assertEquals(0, ticker.read());
    assertEquals(1000000, ticker.read());
    assertEquals(2000000, ticker.read());
  }

  public void testAutoIncrementStep_seconds() {
    FakeTicker ticker = new FakeTicker().setAutoIncrementStep(3, TimeUnit.SECONDS);
    assertEquals(0, ticker.read());

    model = ModelWithCustomEncoder(dt_field=datetime(2019, 1, 1, 8))
    assert jsonable_encoder(model) == {"dt_field": "2019-01-01T08:00:00+00:00"}
    subclass_model = ModelWithCustomEncoderSubclass(dt_field=datetime(2019, 1, 1, 8))
    assert jsonable_encoder(subclass_model) == {"dt_field": "2019-01-01T08:00:00+00:00"}


# TODO: remove when deprecating Pydantic v1
@needs_pydanticv1
def test_encode_custom_json_encoders_model_pydanticv1():

            {"send_key", ""},
            {"recv_key", ""},
            {"shape_inference_graph", shape_inference_graph},
            {"tpu_core", 0},
            {"cost_estimate_ns", 1000000},
            {"shapes", absl::Span<const DataType>({})},
            {"_outside_compilation_subgraph", "O1"},
            {"_xla_token_input_nodes",
             absl::Span<const string>({"_xla_token_arg_node"})},

// because some operating systems place a limit on the number of
// distinct mapped regions per process. As of this writing:
//
//	Darwin    unlimited
//	DragonFly   1000000 (vm.max_proc_mmap)
//	FreeBSD   unlimited
//	Linux         65530 (vm.max_map_count) // TODO: query /proc/sys/vm/max_map_count?
//	NetBSD    unlimited
//	OpenBSD   unlimited
var mmapLimit int32 = 1<<31 - 1