.add(SHORT_NAME, 13.0f)
            .add(LONG_NAME, 14.0f)
            .addValue(15.0f);
      }
    };

    void addEntries(MoreObjects.ToStringHelper helper) {}
  }

  @Param Dataset dataset;

  private static final String SHORT_NAME = "userId";
  private static final String LONG_NAME = "fluxCapacitorFailureRate95Percentile";

  private MoreObjects.ToStringHelper newHelper() {

          .immutableCopy();

  private double[] dataset;

  @Override
  protected void setUp() {
    dataset = new double[DATASET_SIZE];
    for (int i = 0; i < DATASET_SIZE; i++) {
      dataset[i] = rng.nextDouble();
    }
  }

  public void testSingleQuantile_median() {
    double referenceValue = REFERENCE_ALGORITHM.singleQuantile(1, 2, dataset.clone());

            .add(SHORT_NAME, 13.0f)
            .add(LONG_NAME, 14.0f)
            .addValue(15.0f);
      }
    };

    void addEntries(MoreObjects.ToStringHelper helper) {}
  }

  @Param Dataset dataset;

  private static final String SHORT_NAME = "userId";
  private static final String LONG_NAME = "fluxCapacitorFailureRate95Percentile";

  private MoreObjects.ToStringHelper newHelper() {

     */
    public void setEcsServiceName(final String ecsServiceName) {
        this.ecsServiceName = ecsServiceName;
    }

    /**
     * Set the ECS event dataset.
     * @param ecsEventDataset The ECS event dataset.
     */
    public void setEcsEventDataset(final String ecsEventDataset) {
        this.ecsEventDataset = ecsEventDataset;
    }

    }

    @Test
    public void test_setEcsEventDataset() {
        activityHelper.setEcsEventDataset("test-dataset");
        activityHelper.useEcsFormat = true;
        activityHelper.login(OptionalThing.empty());
        assertTrue(localLogMsg.get().contains("\"event.dataset\":\"test-dataset\""));
    }

    @Test
    public void test_setEnvMap() {
        Map<String, String> testEnv = new HashMap<>();

MinIO's Object Lambda implementation allows for transforming your data to serve unique data format requirements for each application. For example, a dataset created by an ecommerce application might include personally identifiable information (PII). When the same data is processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing campaign, you might need to enrich the data with additional details, such as information from the customer loyalty database.

### **4.2 WordCount**

WordCount is a simple program that counts how often a word occurs in a text file. The code builds a dataset of (String, Int) pairs called counts, and saves the dataset to a file.

The following example submits WordCount code to the Scala shell. Select an input file for the Spark WordCount example. We can use any text file as input.

- Login as user **‘spark’**.

        print(statsDetails['BytesScanned'])
        print("Stats details bytesProcessed: ")
        print(statsDetails['BytesProcessed'])
```

## 4. Run the Program

Upload a sample dataset to MinIO using the following commands.

```sh
curl "https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_TotalPopulationBySex.csv" > TotalPopulation.csv
mc mb myminio/mycsvbucket

 *
 * Mappings Data (4,719 bytes)
 * ===========================
 *
 * This is UTF-8 character data. It is indexed into by b2b3 in the ranges dataset.
 *
 * Mappings may overlap.
 *
 * ASCII-Only
 * ==========
 *
 * Neither the section index nor the ranges data use bit 0x80 anywhere. That means the data is

    @Test
    public void test_constructorWithThrowableCause_OutOfMemoryError() {
        // Test that constructor accepts Error as cause (verifies Throwable parameter change)
        String url = "http://example.com/large-dataset";
        String message = "Crawling failed due to memory exhaustion";
        OutOfMemoryError error = new OutOfMemoryError("Heap space exhausted");