* streaming handler is still useful for spark, though there is flink as
alternative
* RDD is also useful for transform especially for non-structure data
* there are many SQL products in market like Drill/Impala, but spark is
more powerful for distributed deployment as far as I know
* we never
Hi,
my comments were for purposes of SQL, also most of other technologies like
snowflake, and Redshift, and using KSQL directly to other sinks quite
easily, without massive engineering, infact databricks is trying to play a
catchup game in this market by coming out with GIU based ETL tools :)
I don't think so. we were using spark integarted with Kafka for
streaming computing and realtime reports. that just works.
SPARK is now just an overhyped and overcomplicated ETL tool, nothing
more, there is another distributed AI called as Ray, which should be the
next billion dollar company
Hi,
SPARK is now just an overhyped and overcomplicated ETL tool, nothing more,
there is another distributed AI called as Ray, which should be the next
billion dollar company instead of just building those features in SPARK
natively using a different computation engine :)
So the only promise of
I am afraid the most sql functions spark has the other BI tools also have.
spark is used for high performance computing, not for SQL function
comparisoin.
Thanks.
In other terms: what analytics funcionality, that no One erp has, Spark offers ?
Hi,
I have a db where are collected sales data Who is managed by Odoo erp. I am
studying Apache Spark (beginner) and I have to show a particular analytics that
Spark can do and that is not supported by erp
In other terms: what analytics funcionality, that no One erp has, Spark offers ?
Thanks
