* that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.
  private static <E extends Comparable<? super E>> SortedSet<E> nullCheckedTreeSet(E[] elements) {
    SortedSet<E> set = newTreeSet();

When deploying applications you will probably want to have some **replication of processes** to take advantage of **multiple cores** and to be able to handle more requests.

As you saw in the previous chapter about [Deployment Concepts](concepts.md){.internal-link target=_blank}, there are multiple strategies you can use.

   * that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.
  private static <E extends Comparable<? super E>> SortedSet<E> nullCheckedTreeSet(E[] elements) {
    SortedSet<E> set = newTreeSet();

streaming compression due to its stability and performance.

This algorithm is specifically optimized for machine generated content.
Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

This means that in cases where raw IO is below these numbers
compression will not only reduce disk usage but also help increase system throughput.

    * Berichten Sie mir, wie Sie FastAPI verwenden (das höre ich gerne).
    * Bekommen Sie mit, wenn ich Ankündigungen mache oder neue Tools veröffentliche.

`max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal...

```
./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.

```

    /**
     * ProjectBuilder parallelism.
     *
     * @since 4.0.0
     */
    @Config(type = "java.lang.Integer", defaultValue = "cores/2 + 1")
    public static final String MAVEN_MODEL_BUILDER_PARALLELISM = "maven.modelBuilder.parallelism";

    /**
     * User property for enabling/disabling the consumer POM feature.
     *
     * @since 4.0.0

Por exemplo:

* **Processamento de áudio** ou **imagem**
* **Visão Computacional**: uma imagem é composta por milhões de pixels, cada pixel tem 3 valores / cores, processar isso normalmente exige alguma computação em todos esses pixels ao mesmo tempo

### Multiple Processes - Workers { #multiple-processes-workers }

If you have more clients than what a single process can handle (for example if the virtual machine is not too big) and you have **multiple cores** in the server's CPU, then you could have **multiple processes** running with the same application at the same time, and distribute all the requests among them.