if (name.equals("physical id")) {
                                currentID = value;
                            }
                            // Number of cores not including hyper-threading
                            if (name.equals("cpu cores")) {
                                assert currentID.isEmpty() == false;
                                socketToCore.put("currentID", Integer.valueOf(value));

import java.util.function.Function;

/**
 * Benchmarks the overhead of constructing {@link Aggregator}s in many
 * parallel threads. Machines with different numbers of cores will see
 * wildly different results running this from running this with more
 * cores seeing more benefits from preallocation.
 */
@Fork(2)
@Warmup(iterations = 10)
@Measurement(iterations = 5)
@BenchmarkMode(Mode.AverageTime)

            .getResolvedConfiguration()
            .getFiles(reallyThirdParty);
        // don't scan provided dependencies that we already scanned, e.x. don't scan cores dependencies for every plugin
        if (compileOnlyConfiguration != null) {
            jars.removeAll(compileOnlyConfiguration);
        }
        return jars;
    }

    @TaskAction

`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...

![hdfs-configs](https://github.com/minio/minio/blob/master/docs/bigdata/images/image2.png?raw=true "hdfs advanced configs")

Navigate to **Custom core-site** to configure MinIO parameters for `_s3a_` connector

![s3a-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image5.png?raw=true "custom core-site")

```
sudo pip install yq
alias kv-pairify='yq ".configuration[]" | jq ".[]" | jq -r ".name + \"=\" + .value"'
```

### 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.

#### Configuration Migration

Map Solr configuration to Fess:

| Solr Feature | Fess Equivalent |
|--------------|----------------|
| Solr Core | Fess doesn't use cores; all documents in one index |
| Schema Fields | Define in crawl configuration or use default fields |
| RequestHandlers | Use Fess JSON API with parameters |
| Facet Fields | Configure in Fess search settings |

    /**
     * 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

------------------------------------------------------------------

=== Load balancing and caches.

By default the tests run on multiple processes using all the available cores on all
available CPUs. Not including hyper-threading.
If you want to explicitly specify the number of JVMs you can do so on the command
line:

----------------------------
./gradlew test -Dtests.jvms=8

process** (e.g. a Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**.

And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled...