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Introducing Apache Spark™ 3.5

Today, we are happy to announce the availability of Apache Spark™ 3.5 on Databricks as part of Databricks Runtime 14.0. We extend our...

Spark Connect Available in Apache Spark 3.4

Last year Spark Connect was introduced at the Data and AI Summit. As part of the recently released Apache SparkTM 3.4, Spark Connect...

Introducing Apache Spark™ 3.4 for Databricks Runtime 13.0

Today, we are happy to announce the availability of Apache Spark™ 3.4 on Databricks as part of Databricks Runtime 13.0 . We extend...

Introducing Apache Spark™ 3.3 for Databricks Runtime 11.0

Today we are happy to announce the availability of Apache Spark™ 3.3 on Databricks as part of Databricks Runtime 11.0 . We want...

Introducing Apache Spark™ 3.2

We are excited to announce the availability of Apache Spark™ 3.2 on Databricks as part of Databricks Runtime 10.0 . We want to...

Introducing Apache Spark™ 3.1

We are excited to announce the availability of Apache Spark 3.1 on Databricks as part of Databricks Runtime 8.0 . We want to...

Improving the Spark Exclusion Mechanism in Databricks

November 6, 2020 by Tianhan Hu, Xingbo Jiang and Xiao Li in
Ed Note: This article contains references to the term blacklist, a term that the Spark community is actively working to remove from Spark...

Interoperability between Koalas and Apache Spark

August 11, 2020 by Takuya Ueshin, Hyukjin Kwon and Xiao Li in
Koalas is an open source project which provides a drop-in replacement for pandas, enabling efficient scaling out to hundreds of worker nodes for...

Introducing Koalas 1.0

June 24, 2020 by Hyukjin Kwon, Takuya Ueshin and Xiao Li in
Koalas was first introduced last year to provide data scientists using pandas with a way to scale their existing big data workloads by...

Introducing Apache Spark 3.0

We’re excited to announce that the Apache Spark TM 3.0.0 release is available on Databricks as part of our new Databricks Runtime 7.0...