*   `tf.data`

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.

				int64(testCase.dataLen), testCase.chunkSize, bytes.NewReader(testCase.data),
				testCase.accessKey, testCase.secretKey)
		case testCase.contentEncoding == "":
			req, err = newTestStreamingSignedRequest(http.MethodPut,
				getPutObjectURL("", testCase.bucketName, testCase.objectName),
				int64(testCase.dataLen), testCase.chunkSize, bytes.NewReader(testCase.data),

        // Test when data length exceeds outputBuffer size
        byte[] buffer = new byte[2000];
        int dataLen = outputBuffer.length + 100; // Exceeds outputBuffer size

        SMBProtocolDecodingException exception =
                assertThrows(SMBProtocolDecodingException.class, () -> response.readDataWireFormat(buffer, 0, dataLen));

        assertEquals("Payload exceeds buffer size", exception.getMessage());
    }

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.

clean, aggr and install. "aggr" is an aggregating task while clean and install are lifecyclephases.
There will be three items in the task list for this dataset.

The stubs also exist at different "levels", where one test might wire stubs into a specific live implementation.
In the next test that same "live implementation" will be used in a stub version instead.

### **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

steners()}var e=t.prototype;return e.enable=function(){this._isEnabled=!0},e.disable=function(){this._isEnabled=!1},e.toggleEnabled=function(){this._isEnabled=!this._isEnabled},e.toggle=function(t){if(this._isEnabled)if(t){var e=this.constructor.DATA_KEY,n=o.default(t.currentTarget).data(e);n||(n=new this.constructor(t.currentTarget,this._getDelegateConfig()),o.default(t.currentTarget).data(e,n)),n._activeTrigger.click=!n._activeTrigger.click,n._isWithActiveTrigger()?n._enter(null,n):n._leave(nu...

 *
 * 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

}

// calculateSignedChunkLength - calculates the length of the overall stream (data + metadata)
func calculateStreamContentLength(dataLen, chunkSize int64) int64 {
	if dataLen <= 0 {
		return 0
	}
	chunksCount := dataLen / chunkSize
	remainingBytes := dataLen % chunkSize
	var streamLen int64
	streamLen += chunksCount * calculateSignedChunkLength(chunkSize)
	if remainingBytes > 0 {