Remove SparkSession from class to prevent it being included in the serialization process

[yalimu-g]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @yalimu-g, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a potential serialization issue within the Spark BigQuery connector's metrics tracking. By marking the SparkSession field as transient, the change ensures that the non-serializable SparkSession object is correctly excluded during serialization, preventing runtime errors. A corresponding test has been added to validate this behavior, enhancing the robustness of the metrics system.

Highlights

• Serialization Fix: The sparkSession field in SparkBigQueryReadSessionMetrics has been marked as transient to prevent it from being included in the serialization process, addressing potential NotSerializableException issues.
• New Test Case: A new test, testSerialization, has been added to SparkBigQueryReadSessionMetricsTest to verify that the metrics class can be successfully serialized and deserialized, ensuring the transient keyword functions as expected.

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[yalimu-g]

/gcbrun

[gemini-code-assist]

Code Review

This pull request correctly identifies and fixes a serialization issue by marking the SparkSession field as transient in SparkBigQueryReadSessionMetrics. This prevents NotSerializableException since SparkSession is not meant to be serialized. The addition of a serialization test is a great way to verify the fix. I've provided a few suggestions to improve the new test case by using try-with-resources for stream handling to prevent resource leaks and by adding more assertions to make the test more comprehensive.

[gemini-code-assist]

To ensure resources are properly managed and to make the code more robust, it's recommended to use a try-with-resources statement for the ObjectOutputStream. This guarantees that the stream is closed even if an exception is thrown.

Suggested change

	java.io.ObjectOutputStream out = new java.io.ObjectOutputStream(bos);
	out.writeObject(metrics);
	out.close();
	try (java.io.ObjectOutputStream out = new java.io.ObjectOutputStream(bos)) {
	out.writeObject(metrics);
	}

[gemini-code-assist]

The ObjectInputStream is not being closed, which can lead to resource leaks in other contexts. It's best practice to use a try-with-resources statement to manage the stream's lifecycle automatically, ensuring it's always closed.

Suggested change

	java.io.ByteArrayInputStream bis = new java.io.ByteArrayInputStream(bos.toByteArray());
	java.io.ObjectInputStream in = new java.io.ObjectInputStream(bis);
	SparkBigQueryReadSessionMetrics deserializedMetrics =
	(SparkBigQueryReadSessionMetrics) in.readObject();
	SparkBigQueryReadSessionMetrics deserializedMetrics;
	try (java.io.ByteArrayInputStream bis = new java.io.ByteArrayInputStream(bos.toByteArray());
	java.io.ObjectInputStream in = new java.io.ObjectInputStream(bis)) {
	deserializedMetrics = (SparkBigQueryReadSessionMetrics) in.readObject();
	}

[gemini-code-assist]

To make the test more thorough, it would be good to also assert that the other metric accumulators (rowsRead, parseTime, scanTime) are correctly initialized to 0 after deserialization. This will provide stronger guarantees about the serialization behavior.

    assertThat(deserializedMetrics.getBytesRead()).isEqualTo(0);
    assertThat(deserializedMetrics.getRowsRead()).isEqualTo(0);
    assertThat(deserializedMetrics.getParseTime()).isEqualTo(0);
    assertThat(deserializedMetrics.getScanTime()).isEqualTo(0);

[yalimu-g]

/gcbrun

[yalimu-g]

/gcbrun