Correct. Also as explained in the book LearningSpark2.0 by Databiricks: Unified Analytics While the notion of unification is not unique to Spark, it is a core component of its design philosophy and evolution. In November 2016, the Association for Computing Machinery (ACM) recognized Apache Spark and conferred upon its original creators the prestigious ACM Award for their paper describing Apache Spark as a “Unified Engine for Big Data Processing.” The award-winning paper notes that Spark replaces all the separate batch processing, graph, stream, and query engines like Storm, Impala, Dremel, Pregel, etc. with a unified stack of components that addresses diverse workloads under a single distributed fast engine.
Khalid > On 19 Oct 2020, at 07:03, Sonal Goyal <sonalgoy...@gmail.com> wrote: > > > My thought is that Spark supports analytics for structured and unstructured > data, batch as well as real time. This was pretty revolutionary when Spark > first came out. That's where the unified term came from I think. Even after > all these years, Spark remains the trusted framework for enterprise > analytics. > >> On Mon, 19 Oct 2020, 11:24 Gourav Sengupta <gourav.sengu...@gmail.com wrote: >> Hi, >> >> I think that it is just a marketing statement. But with SPARK 3.x, now that >> you are seeing that SPARK is no more than just another distributed data >> processing engine, they are trying to join data pre-processing into ML >> pipelines directly. I may call that unified. >> >> But you get the same with several other frameworks as well now so not quite >> sure how unified creates a unique brand value. >> >> >> Regards, >> Gourav Sengupta >> >>> On Sun, Oct 18, 2020 at 6:40 PM Hulio andres <hulioand...@usa.com> wrote: >>> >>> Apache Spark's mission statement is Apache Spark™ is a unified analytics >>> engine for large-scale data processing. >>> >>> To what is the word "unified" inferring ? >>> >>> >>> >>> >>> >>> >>> --------------------------------------------------------------------- To >>> unsubscribe e-mail: user-unsubscr...@spark.apache.org
