* This class provides methods for managing a queue of URLs to be crawled,
 * including adding, deleting, and retrieving URLs from the queue.
 * It uses a {@link MemoryDataHelper} to store the URL queue data in memory.
 *
 * <p>
 * The class is responsible for:
 * </p>
 * <ul>
 *   <li>Updating session IDs for URL queues.</li>
 *   <li>Adding new URLs to the queue.</li>

       - The compressed index.xml file contains a timestamp property which
       changes with every test execution, such that running the test
       actually changes the test classpath itself. This means that it
       can"t benefit from incremental build acceleration, because on every
       execution it sees that the classpath has changed, and so to be
       safe, it needs to re-run.

SuccessExitStatus=143

# Specifies the maximum file descriptor number that can be opened by this process
LimitNOFILE=${packaging.os.max.open.files}

# Specifies the maximum number of bytes of memory that may be locked into RAM
# Set to "infinity" if you use the 'bootstrap.mlockall: true' option
# in fess.yml and 'MAX_LOCKED_MEMORY=unlimited' in ${packaging.env.file}
#LimitMEMLOCK=infinity

//
// CreateRaw's argument is stored in w. If the argument is a pointer to the embedded
// [FileHeader] in a [File] obtained from a [Reader] created from in-memory data,
// then w will refer to all of that memory.
func (w *Writer) CreateRaw(fh *FileHeader) (io.Writer, error) {
	if err := w.prepare(fh); err != nil {
		return nil, err
	}

  // ExtendSessionGraphHelper manually.
  std::atomic<bool> extend_before_run;
};

struct TF_ImportGraphDefOptions {
  tensorflow::ImportGraphDefOptions opts;

  // Backing memory for TensorId fields in opts.
  // TODO(skyewm): it'd be better if ImportGraphDefOptions owned this.
  std::vector<tensorflow::string> tensor_id_data;
};

struct TF_ImportGraphDefResults {

    Fire<V> fire = new Fire<>(result);
    result.timer = scheduledExecutor.schedule(fire, time, unit);
    delegate.addListener(fire, directExecutor());
    return result;
  }

  /*
   * Memory visibility of these fields. There are two cases to consider.
   *
   * 1. visibility of the writes to these fields to Fire.run:
   *
   * The initial write to delegateRef is made definitely visible via the semantics of

 */
final class Platform {
  static CharMatcher precomputeCharMatcher(CharMatcher matcher) {
    // CharMatcher.precomputed() produces CharMatchers that are maybe a little
    // faster (and that's debatable), but definitely more memory-hungry. We're
    // choosing to turn .precomputed() into a no-op in GWT, because it doesn't
    // seem to be a worthwhile tradeoff in a browser.
    return matcher;
  }

instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
target/

# Jupyter Notebook
.ipynb_checkpoints

# pyenv
.python-version

# celery beat schedule file
celerybeat-schedule

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

      disable: true # optionally turn-off snowball archive transfer
#      batch: 100 # upto this many objects per archive
#      inmemory: true # indicates if the archive must be staged locally or in-memory
#      compress: false # S2/Snappy compressed archive
#      smallerThan: 5MiB # create archive for all objects smaller than 5MiB
#      skipErrs: false # skips any source side read() errors