or destruction of data or any other property which may arise from
> relying on this email's technical content is explicitly disclaimed. The
> author will in no case be liable for any monetary damages arising from such
> loss, damage or destruction.
>
>
>
> On Fri, 14
gt; on your Spark cluster.
More details can be found in our blog
<https://hbutani.github.io/blogs/blog/Spark_on_Oracle_Blog.html> and
the project
wiki. <https://github.com/oracle/spark-oracle/wiki>
regards,
Harish Butani
, comments from the Spark community.
regards,
Harish Butani.
utani/spark-sql-macros/wiki/Spark_SQL_Macro_examples)
provides even more examples.
regards,
Harish Butani.
BTW, we now support OLAP functionality natively in spark w/o the need for
Druid, through our Spark native BI platform(SNAP):
https://www.linkedin.com/pulse/integrated-business-intelligence-big-data-stacks-harish-butani
- we provide SQL commands to: create star schema, create olap index, and
Hi,
I have just posted a Blog on this:
https://www.linkedin.com/pulse/combining-druid-spark-interactive-flexible-analytics-scale-butani
regards,
Harish Butani.
On Tue, Sep 1, 2015 at 11:46 PM, Paolo Platter
wrote:
> Fantastic!!! I will look into that and I hope to contribute
>
&
ign document, which also describes a benchmark of
representative queries on the TPCH dataset.
Looking for folks who would be willing to try this out and/or contribute.
regards,
Harish Butani.
Yes via: org.apache.spark.sql.catalyst.optimizer.ColumnPruning
See DefaultOptimizer.batches for list of logical rewrites.
You can see the optimized plan by printing: df.queryExecution.optimizedPlan
On Mon, Jul 20, 2015 at 5:22 PM, Mohammed Guller
wrote:
> Michael,
>
> How would the Catalyst o
Can you post details on how to reproduce the NPE
On Mon, Jul 20, 2015 at 1:19 PM, algermissen1971 wrote:
> Hi Harish,
>
> On 20 Jul 2015, at 20:37, Harish Butani wrote:
>
> > Hey Jan,
> >
> > Can you provide more details on the serialization and cache issues.
&
Hey Jan,
Can you provide more details on the serialization and cache issues.
If you are looking for datetime functionality with spark-sql please
consider: https://github.com/SparklineData/spark-datetime It provides a
simple way to combine joda datetime expressions with spark sql.
regards,
Haris
Just once.
You can see this by printing the optimized logical plan.
You will see just one repartition operation.
So do:
val df = sql("your sql...")
println(df.queryExecution.analyzed)
On Mon, Jul 13, 2015 at 6:37 AM, Hao Ren wrote:
> Hi,
>
> I would like to know: Is there any optimization has b
try the spark-datetime package:
https://github.com/SparklineData/spark-datetime
Follow this example
https://github.com/SparklineData/spark-datetime#a-basic-example to get the
different attributes of a DateTime.
On Wed, Jul 8, 2015 at 9:11 PM, prosp4300 wrote:
> As mentioned in Spark sQL programm
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