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

  }

  /*
   * The maximum number of bits in a square root for which we'll precompute an explicit half power
   * of two. This can be any value, but higher values incur more class load time and linearly
   * increasing memory consumption.
   */
  @VisibleForTesting static final int SQRT2_PRECOMPUTE_THRESHOLD = 256;

  @VisibleForTesting
  static final BigInteger SQRT2_PRECOMPUTED_BITS =

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

	if err != nil && !errors.Is(err, errConfigNotFound) {
		return err
	}

	z.rebalMu.Lock()
	defer z.rebalMu.Unlock()

	// if not found, we store the memory metadata back
	// when rebalance status changed, will notify all nodes update status to memory, we can treat the memory metadata is the latest status
	if errors.Is(err, errConfigNotFound) {
		r = z.rebalMeta
	}

	switch opts {
	case rebalSaveStoppedAt:

      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

```
./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.

```

    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;
  }

   * response body. Call `body.source().request(1024 * 1024)` to block until either that's done, or
   * 1 MiB of response data is loaded into memory. (You could use any size here, though large values
   * risk exhausting memory.)
   *
   * This returns an empty value if the trailers are available, but have no data.
   *

- Fluent API for building HTTP requests (GET, POST, PUT, DELETE, HEAD, OPTIONS, CONNECT, TRACE)
- Support for query parameters, headers, body (String or stream), compression, SSL configuration, proxies, and timeouts
- Automatic in-memory or on-disk caching of request/response bodies
- Synchronous and asynchronous (callback) execution
- Minimal dependencies (only Apache Commons IO)

## Installation

### Maven