![]() ![]() To enable the reader, users can set to native. Vectorized ORC Reader: Adds support for new ORC reader that substantially improves the ORC scan throughput through vectorization (2-5x).Note that this support is currently experimental and behavioral changes around configurations, container images and entrypoints should be expected. Spark on Kubernetes: A new kubernetes scheduler backend that supports native submission of spark jobs to a cluster managed by kubernetes. ![]() We have curated a list of high level changes here, grouped by major modules. You can consult JIRA for the detailed changes. ![]() ![]() To download Apache Spark 2.3.0, visit the downloads page. In addition, this release continues to focus on usability, stability, and polish while resolving around 1400 tickets. Other major updates include the new DataSource and Structured Streaming v2 APIs, and a number of PySpark performance enhancements. This release adds support for Continuous Processing in Structured Streaming along with a brand new Kubernetes Scheduler backend. Report bugs HERE. Write a testimonial HERE, if you'd like to share your experiences in our testimonials section.Apache Spark 2.3.0 is the fourth release in the 2.x line. Please do consider donatingif QuickHash-GUI is useful to you. This new version includes some fixes to the v3.3 branch and is v3.3.1. But on a 32-bit Windows machine, only the 32-bit edition will work. The user can run both the 32 and 64 bit executables on a single Windows 64 machine, even at the same time. On most Windows systems, if the user extracts the whole zip file (including the new "libs" folder) to a new folder or their desktop, it should just run. which should obviously be run on the appropriate Windows system for best effect. The download includes both a 64-bit and 32-bit edition of the software with accompanying DLL's and user manual (in English - a French version is currently available too for French speaking users, HERE). This download is for the Windows version of Quickhash-GUI. ![]()
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