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Engine Kernel Version

Last updated: 2024-07-31 17:47:29
DLC provides different kernel versions optimized for various use cases, with numerous features and performance enhancements. The available kernel versions are listed below.
If your scenario primarily involves interactive queries, it is recommended to use the Presto engine and SparkSQL engine with the latest kernel versions.
If your scenario primarily involves batch jobs, it is recommended to use the Spark job engine with the Spark 3.2 kernel version.
Engine Type
Kernel Version
Description
Presto
SuperSQL-P 1.0
Based on the native Presto 0.242 version, this implementation supports dynamic data source loading, enhanced Dynamic Filter, Iceberg V2 tables, INSERT OVERWRITE for non-partitioned tables, and execution of Hive UDFs.
SparkSQL
SuperSQL-S 1.0
Based on the native Spark 3.2 version, this implementation supports Iceberg 1.1.0, Hudi 0.12.0, and Adaptive Shuffle Manager.
SuperSQL-S 3.5
Based on the native Spark3.5 version, this implementation supports Iceberg 1.5.0 and Adaptive Shuffle Manager.
The current beta version is backward compatible with various SQL and data governance tasks of SuperSQL-S 1.0, providing a performance improvement of more than 33% over the S1.0 version.
SparkBatch
Spark 3.5
Based on the native Spark3.5 version, this implementation supports Iceberg 1.5.0, Python3 and Adaptive Shuffle Manager.
The current beta version is backward compatible with various SQL, jar, pyspark and data governance tasks of Spark 3.2, with a performance improvement of more than 33% over Spark 3.2.
Spark 3.2
Based on the original Spark3.2 version, this implementation supports Iceberg 1.1.0, Hudi 0.12.0, Python3, and Adaptive Shuffle Manager.
Spark 2.4
Based on the native Spark2.4 version, this implementation supports Iceberg 0.13.1, Python2, and Python3.

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