[Snyk] Security upgrade org.apache.spark:spark-core_2.12 from 3.5.1 to 3.5.8

[snyk-io]

Snyk has created this PR to fix 1 vulnerabilities in the maven dependencies of this project.

Snyk changed the following file(s):

• pom.xml

Vulnerabilities that will be fixed with an upgrade:

	Issue	Score	Upgrade
	Race Condition SNYK-JAVA-ORGGLASSFISHJERSEYCORE-14049172	249	org.apache.spark:spark-core_2.12: 3.5.1 -> 3.5.8 No Path Found Proof of Concept

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🦉 Race Condition

[snyk-io]

This is a patch-level update from 3.5.1 to 3.5.8. Apache Spark's patch releases are for bug and security fixes and are designed to be backward-compatible. The release notes for versions within this range confirm they are maintenance releases with no breaking API changes.

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

✅ Snyk checks have passed. No issues have been found so far.

Status	Scanner	Critical	High	Medium	Low	Total (0)
✅	Open Source Security	0	0	0	0	0 issues
✅	Licenses	0	0	0	0	0 issues

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[snyk-io]

This is a maintenance release consisting of security and correctness fixes. The risk of breaking changes is low.

A minor behavior correction was noted for a specific data source. Since Spark 3.5.2, the MySQL JDBC datasource reads TINYINT UNSIGNED as ShortType, correcting a bug in version 3.5.1 where it was read as ByteType. Applications using MySQL TINYINT UNSIGNED columns may be affected by this type change.

Recommendation: It is safe to merge this upgrade. Most applications will be unaffected, but users of MySQL data sources should verify behavior if they use TINYINT UNSIGNED columns.

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a patch-level upgrade within the same minor version (3.5.x). According to Apache Spark's versioning policy, these releases are for bug fixes and should not contain breaking API changes. The update from 3.5.1 to 3.5.8 focuses on stability and performance improvements.

Source: Apache Spark Release Notes

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a patch upgrade within the same minor version series. According to Apache Spark's release policy, these maintenance releases contain only security and correctness fixes and are designed to be fully backward-compatible. No breaking changes are expected.

Source: Apache Spark documentation

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a patch-level upgrade within the same minor version of Apache Spark. The releases from 3.5.2 to 3.5.8 consist of maintenance releases containing security and correctness fixes. No breaking API changes are expected.

Source: Apache Spark Release Notes

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a maintenance release that contains security and correctness fixes. Based on the official release notes, no breaking changes are expected between these versions.

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a maintenance upgrade within the same minor version, consisting of bug and security fixes. Apache Spark's release notes confirm that patch releases in the 3.5.x series are for stability and correctness, with no major breaking changes cited between 3.5.1 and 3.5.8. [1, 2]

Highlight:

• A minor change in error handling was introduced in version 3.5.4: when reading SQL tables, certain Hadoop exceptions will now fail the task even if spark.sql.files.ignoreCorruptFiles is true. [7]

Source: Apache Spark documentation
Recommendation: This upgrade is safe to merge. The risk of breaking changes is minimal as it is a maintenance release path.

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.

[snyk-io]

This is a maintenance release upgrade within the same minor version series. According to Apache Spark's versioning policy, these releases contain security and correctness fixes and are not expected to have breaking changes.

Source: Apache Spark Release Documentation

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.