Bump io.delta:delta-kernel-api from 4.1.0 to 4.2.0

[dependabot]

Bumps io.delta:delta-kernel-api from 4.1.0 to 4.2.0.

Release notes

Sourced from io.delta:delta-kernel-api's releases.

Delta Lake 4.2.0

We are excited to announce the release of Delta Lake 4.2.0! This release includes significant new features, improved safety and compatibility, and important bug fixes.

Highlights

• [Spark] Unity Catalog Managed Table enhancements: REPLACE TABLE / RTAS and Dynamic Partition Overwrite support, automatic table schema/properties sync to catalog on table creation.
• [Spark] Delta Spark V2 connector - streaming read (experimental): enhance streaming read capabilities for catalog-managed table by supporting critical options like startingTimestamp and skipChangeCommits.
• [Flink] New Kernel-based Flink connector (experimental): a brand-new Kernel-based delta-flink connector that enables Apache Flink to read, write, and interact with catalog-managed Delta tables.
• [Kernel] Geospatial, Variant GA, and Collations table feature: Delta Kernel can now read and write tables using geometry/geography types with bounding-box data skipping, generally available Variant columns, and collated string types.
• [Security] The Delta project has undergone a substantial hardening effort across multiple surface areas, including stronger validation and dependency security scanning to proactively reduce supply-chain risk.

Delta Spark

Delta Spark 4.2.0 is built on Apache Spark 4.1.0 and Apache Spark 4.0.1. Similar to Apache Spark, we have released Maven artifacts for Scala 2.13.

• Maven artifacts for Spark 4.1.0:
  • delta-spark_4.1_2.13
  • delta-connect-client_4.1_2.13
  • delta-connect-common_4.1_2.13
  • delta-connect-server_4.1_2.13
  • delta_contribs_2.13
  • delta-storage
  • delta-storage-s3-dynamodb
• Maven artifacts for Spark 4.0.1:
  • delta-spark_4.0_2.13
  • delta-connect-client_4.0_2.13
  • delta-connect-common_4.0_2.13
  • delta-connect-server_4.0_2.13
  • delta_contribs_2.13
  • delta-storage
  • delta-storage-s3-dynamodb
• Backward compatibility artifacts - no spark version in name and work with Spark 4.1.0:
  • delta-spark_2.13
  • delta-connect-client_2.13
  • delta-connect-common_2.13
  • delta-connect-server_2.13
• Python artifacts: https://pypi.org/project/delta-spark/4.2.0/

The key features of this release are:

• Delta Spark V2 Streaming read: Enhance streaming read capabilities for catalog-managed tables. The Delta V2 Spark connector now supports key options including startingVersion, startingTimestamp, maxBytesPerTrigger, maxFilesPerTrigger, excludeRegex, skipChangeCommits, ignoreDeletes, ignoreChanges, and ignoreFileDeletion.
• REPLACE TABLE/RTAS/DPO support: Previously, operations like REPLACE TABLE, RTAS, and Dynamic Partition Overwrite (DPO) were not supported for catalog-managed Delta tables. This change will enable these operations to be a single, atomic action, significantly improving the safety and reliability of users' catalog-managed tables.
• Server-Side Planning: OAuth Support (preview): The server-side planning client now supports OAuth-based authentication when delegating scan planning to an external catalog server.
• INSERT BY NAME with Schema Evolution: SQL INSERT ... BY NAME statements now support automatic schema evolution, adding missing columns to the target table when delta.schemaAutoMerge.enabled is set. This brings INSERT BY NAME behavior in line with INSERT SELECT with schema evolution.
• Force Statistics Collection: A new table property delta.stats.skipping.forceOptimizeStatsCollection enables forcing file statistics collection during query optimization. This ensures accurate data skipping for tables where statistics may be absent or stale, without requiring a manual OPTIMIZE run.
• Allow CDF Writes for Non-Data-Changing Operations: When Change Data Feed is enabled, write operations that produce no data changes — such as add-only or remove-only commits — are now permitted. This reduces unnecessary write failures in CDC pipelines that perform metadata-only or compaction operations.
• Variant Type in Schema Conversion: Delta Spark now correctly handles Spark's VariantType during Delta schema conversion, enabling seamless schema operations on tables with Variant columns.

Other notable changes:

... (truncated)

Commits

• 9f600c4 Setting version to 4.2.0
• 194e707 [Build] Fix the iceberg scalastyle checks and fix the integration failures (#...
• 88eac9d [Build] Bump parquet-avro in hudi module to fix ConvertToHudiSuite on master ...
• 6f7a312 [Kernel] Support def value in v3 (#6532)
• 1d91826 [Delta] Reclassify DELTA_METADATA_ABSENT_EXISTING_CATALOG_TABLE (#6527)
• efa5155 [kernel-spark][Part 2] CDC commit processing (convert delta log actions to In...
• ff48afb SparkScan: skip catalog stats branch when numRows is absent (#6528)
• 5252e32 [Kernel] Geospatial Parquet support: read/write geometry/geography as WKB wit...
• 9a82a76 [Flink] Run flink github workflow only on changes in kernel/flink folder (#6524)
• ac5f430 [UniForm] Fix field ID assignment for schema during initial Delta->Iceberg co...
• Additional commits viewable in compare view

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