After installing Hive, Hadoop and Spark successfully, we can now proceed to run some sample applications to see if they are configured appropriately.  We can use Spark Pi and Spark WordCount programs to validate our Spark installation. We can also explore how to run Spark jobs from the command line and Spark shell.

### **4.1 Spark Pi**

        .address.url.host
    ) {
      return true // This connection is a perfect match.
    }

    // At this point we don't have a hostname match. But we still be able to carry the request if
    // our connection coalescing requirements are met. See also:
    // https://hpbn.co/optimizing-application-delivery/#eliminate-domain-sharding
    // https://daniel.haxx.se/blog/2016/08/18/http2-connection-coalescing/

            exclude_unset=exclude_unset,
            exclude_defaults=exclude_defaults,
            exclude_none=exclude_none,
        )

    def __hash__(self) -> int:
        # Each ModelField is unique for our purposes, to allow making a dict from
        # ModelField to its JSON Schema.
        return id(self)


def _has_computed_fields(field: ModelField) -> bool:

     */
    @SuppressWarnings("nullness")
    Object[] result = ObjectArrays.toArrayImpl(this);
    return result;
  }

  @Override
  @SuppressWarnings("nullness") // b/192354773 in our checker affects toArray declarations
  public <T extends @Nullable Object> T[] toArray(T[] other) {
    return ObjectArrays.toArrayImpl(this, other);
  }

  @Override

        collect.forEach(consumer::accept);
    }

    private String getGradleProjectPathFor(Version version) {
        // We have Gradle projects set up to check out and build unreleased versions based on the our branching
        // conventions described in this classes javadoc
        if (version.equals(currentVersion)) {
            return ":distribution";
        }

                            || message.contains("unregistered")));
        }
    }

    /**
     * Test that all registered types work correctly.
     * This ensures our registration covers the common use cases.
     */
    @Test
    public void test_allRegisteredTypesWork() {
        // Test various registered types
        Map<String, Object> testData = new HashMap<>();

        }
    }

    private class TestableIndexUpdateCallbackImpl extends IndexUpdateCallbackImpl {
        @PostConstruct
        @Override
        public void init() {
            // Override init to use our test config directly
            maxDocumentRequestSize = 1048576L;
            maxDocumentCacheSize = 10000;
            // Set ingestFactory using reflection since it's private

  }

  @Override
  public final @Nullable V getOrDefault(@Nullable Object key, @Nullable V defaultValue) {
    V result = get(key);
    // TODO(b/192579700): Use a ternary once it no longer confuses our nullness checker.
    if (result != null) {
      return result;
    } else {
      return defaultValue;
    }
  }

  private transient @Nullable ImmutableSet<Entry<K, V>> cachedEntrySet = null;

             * A word about communicating header info to andx smbs
             *
             * This is where we recursively invoke the provided andx smb
             * object to write it's parameter words and bytes to our outgoing
             * array. Incedentally when these andx smbs are created they are not
             * necessarily populated with header data because they're not writing

In the same server (or servers), there could be **multiple applications**, for example, other API programs or a database.

Only one process can be handling the specific IP and port (the TLS Termination Proxy in our example) but the other applications/processes can be running on the server(s) too, as long as they don't try to use the same **combination of public IP and port**.

<img src="/img/deployment/https/https08.drawio.svg">