utani/spark-sql-macros/wiki/Spark_SQL_Macro_examples)
provides even more examples.
regards,
Harish Butani.
, comments from the Spark community.
regards,
Harish Butani.
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
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
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
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
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
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.
&
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
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.
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
>
&
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
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