![]() ![]() Support complex types for Parquet vectorized reader. ( SPARK-38860)Įrror message improvements to identify problems faster and take the necessary steps to resolve them. Improve the compatibility of Spark with the SQL standard: ANSI enhancements. Row-level filtering: improve the performance of joins by prefiltering one side, as long as there are no deprecation or regression impacts on using a Bloom filter and IN predicate generated from the values from the other side of the join. New features and improvements Apache Spark 3.3.1įollowing is an extended summary of key new features related to Apache Spark version 3.3.0 and 3.3.1: ![]() Staying up to date ensures optimal performance and reliability for your data processing tasks. Microsoft Fabric periodically rolls out maintenance updates for Runtime 1.1, providing bug fixes, performance enhancements, and security patches. Refer to the documentation for a complete list of libraries. These libraries are automatically included when using notebooks or jobs in the Microsoft Fabric platform. Microsoft Fabric Runtime 1.1 comes with a collection of default level packages, including a full Anaconda installation and commonly used libraries for Java/Scala, Python, and R. ![]() Microsoft Fabric Runtime 1.1 is the default and currently the only runtime offered within the Microsoft Fabric platform. The Microsoft Fabric Runtime is built upon a robust open-source operating system (Ubuntu), ensuring compatibility with various hardware configurations and system requirements. These packages are automatically installed and configured, allowing developers to apply their preferred programming languages for data processing tasks. Integrated within the Microsoft Fabric Runtime, Delta Lake enhances the data processing capabilities and ensures data consistency across multiple concurrent operations.ĭefault-level Packages for Java/Scala, Python, and R to support diverse programming languages and environments. Apache Spark provides a versatile and high-performance platform for data engineering and data science experiences.ĭelta Lake - an open-source storage layer that brings ACID transactions and other data reliability features to Apache Spark. Apache Spark - a powerful open-source distributed computing library, to enable large-scale data processing and analytics tasks. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |