subject:"Re\: sql to spark scala rdd"

Re: sql to spark scala rdd

2016-08-02 Thread Sri

Make sense thanks.

Thanks
Sri

Sent from my iPhone

> On 2 Aug 2016, at 03:27, Jacek Laskowski  wrote:
> 
> Congrats!
> 
> Whenever I was doing foreach(println) in the past I'm .toDF.show these
> days. Give it a shot and you'll experience the feeling yourself! :)
> 
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
> 
> 
> On Tue, Aug 2, 2016 at 4:25 AM, sri hari kali charan Tummala
>  wrote:
>> Hi All,
>> 
>> Below code calculates cumulative sum (running sum) and moving average using
>> scala RDD type of programming, I was using wrong function which is sliding
>> use scalleft instead.
>> 
>> 
>> sc.textFile("C:\\Users\\kalit_000\\Desktop\\Hadoop_IMP_DOC\\spark\\data.txt")
>>  .map(x => x.split("\\~"))
>>  .map(x => (x(0), x(1), x(2).toDouble))
>>  .groupBy(_._1)
>>  .mapValues{(x => x.toList.sortBy(_._2).zip(Stream from
>> 1).scanLeft(("","",0.0,0.0,0.0,0.0))
>>  { (a,b) => (b._1._1,b._1._2,b._1._3,(b._1._3.toDouble +
>> a._3.toDouble),(b._1._3.toDouble + a._3.toDouble)/b._2,b._2)}.tail)}
>>  .flatMapValues(x => x.sortBy(_._1))
>>  .foreach(println)
>> 
>> Input Data:-
>> 
>> Headers:-
>> Key,Date,balance
>> 
>> 786~20160710~234
>> 786~20160709~-128
>> 786~20160711~-457
>> 987~20160812~456
>> 987~20160812~567
>> 
>> Output Data:-
>> 
>> Column Headers:-
>> key, (key,Date,balance , daily balance, running average , row_number based
>> on key)
>> 
>> (786,(786,20160709,-128.0,-128.0,-128.0,1.0))
>> (786,(786,20160710,234.0,106.0,53.0,2.0))
>> (786,(786,20160711,-457.0,-223.0,-74.33,3.0))
>> 
>> (987,(987,20160812,567.0,1023.0,511.5,2.0))
>> (987,(987,20160812,456.0,456.0,456.0,1.0))
>> 
>> Reference:-
>> 
>> https://bzhangusc.wordpress.com/2014/06/21/calculate-running-sums/
>> 
>> 
>> Thanks
>> Sri
>> 
>> 
>>> On Mon, Aug 1, 2016 at 12:07 AM, Sri  wrote:
>>> 
>>> Hi ,
>>> 
>>> I solved it using spark SQL which uses similar window functions mentioned
>>> below , for my own knowledge I am trying to solve using Scala RDD which I am
>>> unable to.
>>> What function in Scala supports window function like SQL unbounded
>>> preceding and current row ? Is it sliding ?
>>> 
>>> 
>>> Thanks
>>> Sri
>>> 
>>> Sent from my iPhone
>>> 
>>> On 31 Jul 2016, at 23:16, Mich Talebzadeh 
>>> wrote:
>>> 
>>> hi
>>> 
>>> You mentioned:
>>> 
>>> I already solved it using DF and spark sql ...
>>> 
>>> Are you referring to this code which is a classic analytics:
>>> 
>>> SELECT DATE,balance,
>>> 
>>> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>>> 
>>> AND
>>> 
>>> CURRENT ROW) daily_balance
>>> 
>>> FROM  table
>>> 
>>> 
>>> So how did you solve it using DF in the first place?
>>> 
>>> 
>>> HTH
>>> 
>>> 
>>> Dr Mich Talebzadeh
>>> 
>>> 
>>> 
>>> LinkedIn
>>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>>> 
>>> 
>>> 
>>> http://talebzadehmich.wordpress.com
>>> 
>>> 
>>> Disclaimer: Use it at your own risk. Any and all responsibility for any
>>> loss, damage 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 1 August 2016 at 07:04, Sri  wrote:
 
 Hi ,
 
 Just wondering how spark SQL works behind the scenes does it not convert
 SQL to some Scala RDD ? Or Scala ?
 
 How to write below SQL in Scala or Scala RDD
 
 SELECT DATE,balance,
 
 SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
 
 AND
 
 CURRENT ROW) daily_balance
 
 FROM  table
 
 
 Thanks
 Sri
 Sent from my iPhone
 
 On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
 
 Hi,
 
 Impossible - see
 
 http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr].
 
 I tried to show you why you ended up with "non-empty iterator" after
 println. You should really start with
 http://www.scala-lang.org/documentation/
 
 Pozdrawiam,
 Jacek Laskowski
 
 https://medium.com/@jaceklaskowski/
 Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
 Follow me at https://twitter.com/jaceklaskowski
 
 
 On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
  wrote:
 
 Tuple
 
 
 [Lscala.Tuple2;@65e4cb84
 
 
 On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
 
 
 Hi,
 
 
 What's the result type of sliding(2,1)?
 
 
 Pozdrawiam,
 
 Jacek

Re: sql to spark scala rdd

2016-08-02 Thread Jacek Laskowski

Congrats!

Whenever I was doing foreach(println) in the past I'm .toDF.show these
days. Give it a shot and you'll experience the feeling yourself! :)

Pozdrawiam,
Jacek Laskowski

https://medium.com/@jaceklaskowski/
Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
Follow me at https://twitter.com/jaceklaskowski


On Tue, Aug 2, 2016 at 4:25 AM, sri hari kali charan Tummala
 wrote:
> Hi All,
>
> Below code calculates cumulative sum (running sum) and moving average using
> scala RDD type of programming, I was using wrong function which is sliding
> use scalleft instead.
>
>
> sc.textFile("C:\\Users\\kalit_000\\Desktop\\Hadoop_IMP_DOC\\spark\\data.txt")
>   .map(x => x.split("\\~"))
>   .map(x => (x(0), x(1), x(2).toDouble))
>   .groupBy(_._1)
>   .mapValues{(x => x.toList.sortBy(_._2).zip(Stream from
> 1).scanLeft(("","",0.0,0.0,0.0,0.0))
>   { (a,b) => (b._1._1,b._1._2,b._1._3,(b._1._3.toDouble +
> a._3.toDouble),(b._1._3.toDouble + a._3.toDouble)/b._2,b._2)}.tail)}
>   .flatMapValues(x => x.sortBy(_._1))
>   .foreach(println)
>
> Input Data:-
>
> Headers:-
> Key,Date,balance
>
> 786~20160710~234
> 786~20160709~-128
> 786~20160711~-457
> 987~20160812~456
> 987~20160812~567
>
> Output Data:-
>
> Column Headers:-
> key, (key,Date,balance , daily balance, running average , row_number based
> on key)
>
> (786,(786,20160709,-128.0,-128.0,-128.0,1.0))
> (786,(786,20160710,234.0,106.0,53.0,2.0))
> (786,(786,20160711,-457.0,-223.0,-74.33,3.0))
>
> (987,(987,20160812,567.0,1023.0,511.5,2.0))
> (987,(987,20160812,456.0,456.0,456.0,1.0))
>
> Reference:-
>
> https://bzhangusc.wordpress.com/2014/06/21/calculate-running-sums/
>
>
> Thanks
> Sri
>
>
> On Mon, Aug 1, 2016 at 12:07 AM, Sri  wrote:
>>
>> Hi ,
>>
>> I solved it using spark SQL which uses similar window functions mentioned
>> below , for my own knowledge I am trying to solve using Scala RDD which I am
>> unable to.
>> What function in Scala supports window function like SQL unbounded
>> preceding and current row ? Is it sliding ?
>>
>>
>> Thanks
>> Sri
>>
>> Sent from my iPhone
>>
>> On 31 Jul 2016, at 23:16, Mich Talebzadeh 
>> wrote:
>>
>> hi
>>
>> You mentioned:
>>
>> I already solved it using DF and spark sql ...
>>
>> Are you referring to this code which is a classic analytics:
>>
>> SELECT DATE,balance,
>>
>>  SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>>
>>  AND
>>
>>  CURRENT ROW) daily_balance
>>
>>  FROM  table
>>
>>
>> So how did you solve it using DF in the first place?
>>
>>
>> HTH
>>
>>
>> Dr Mich Talebzadeh
>>
>>
>>
>> LinkedIn
>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>>
>>
>>
>> http://talebzadehmich.wordpress.com
>>
>>
>> Disclaimer: Use it at your own risk. Any and all responsibility for any
>> loss, damage 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 1 August 2016 at 07:04, Sri  wrote:
>>>
>>> Hi ,
>>>
>>> Just wondering how spark SQL works behind the scenes does it not convert
>>> SQL to some Scala RDD ? Or Scala ?
>>>
>>> How to write below SQL in Scala or Scala RDD
>>>
>>> SELECT DATE,balance,
>>>
>>> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>>>
>>> AND
>>>
>>> CURRENT ROW) daily_balance
>>>
>>> FROM  table
>>>
>>>
>>> Thanks
>>> Sri
>>> Sent from my iPhone
>>>
>>> On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
>>>
>>> Hi,
>>>
>>> Impossible - see
>>>
>>> http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr].
>>>
>>> I tried to show you why you ended up with "non-empty iterator" after
>>> println. You should really start with
>>> http://www.scala-lang.org/documentation/
>>>
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>>
>>>
>>> On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
>>>  wrote:
>>>
>>> Tuple
>>>
>>>
>>> [Lscala.Tuple2;@65e4cb84
>>>
>>>
>>> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>>>
>>>
>>> Hi,
>>>
>>>
>>> What's the result type of sliding(2,1)?
>>>
>>>
>>> Pozdrawiam,
>>>
>>> Jacek Laskowski
>>>
>>> 
>>>
>>> https://medium.com/@jaceklaskowski/
>>>
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>>
>>> Follow me at https://twitter.com/jaceklaskowski
>>>
>>>
>>>
>>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>>
>>>  wrote:
>>>
>>> tried this no luck, wht is non-empty iterator here ?
>>>
>>>
>>> OP:-
>>>
>>>

Re: sql to spark scala rdd

2016-08-01 Thread sri hari kali charan Tummala

Hi All,

Below code calculates cumulative sum (running sum) and moving average using
scala RDD type of programming, I was using wrong function which is sliding
use scalleft instead.


sc.textFile("C:\\Users\\kalit_000\\Desktop\\Hadoop_IMP_DOC\\spark\\data.txt")
  .map(x => x.split("\\~"))
  .map(x => (x(0), x(1), x(2).toDouble))
  .groupBy(_._1)
  .mapValues{(x => x.toList.sortBy(_._2).zip(Stream from
1).scanLeft(("","",0.0,0.0,0.0,0.0))
  { (a,b) => (b._1._1,b._1._2,b._1._3,(b._1._3.toDouble +
a._3.toDouble),(b._1._3.toDouble + a._3.toDouble)/b._2,b._2)}.tail)}
  .flatMapValues(x => x.sortBy(_._1))
  .foreach(println)

Input Data:-

Headers:-
Key,Date,balance

786~20160710~234
786~20160709~-128
786~20160711~-457
987~20160812~456
987~20160812~567

Output Data:-

Column Headers:-
key, (key,Date,balance , daily balance, running average , row_number based
on key)

(786,(786,20160709,-128.0,-128.0,-128.0,1.0))
(786,(786,20160710,234.0,106.0,53.0,2.0))
(786,(786,20160711,-457.0,-223.0,-74.33,3.0))

(987,(987,20160812,567.0,1023.0,511.5,2.0))
(987,(987,20160812,456.0,456.0,456.0,1.0))

Reference:-

https://bzhangusc.wordpress.com/2014/06/21/calculate-running-sums/


Thanks
Sri


On Mon, Aug 1, 2016 at 12:07 AM, Sri  wrote:

> Hi ,
>
> I solved it using spark SQL which uses similar window functions mentioned
> below , for my own knowledge I am trying to solve using Scala RDD which I
> am unable to.
> What function in Scala supports window function like SQL unbounded
> preceding and current row ? Is it sliding ?
>
>
> Thanks
> Sri
>
> Sent from my iPhone
>
> On 31 Jul 2016, at 23:16, Mich Talebzadeh 
> wrote:
>
> hi
>
> You mentioned:
>
> I already solved it using DF and spark sql ...
>
> Are you referring to this code which is a classic analytics:
>
> SELECT DATE,balance,
>  SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>
>  AND
>
>  CURRENT ROW) daily_balance
>
>  FROM  table
>
>
> So how did you solve it using DF in the first place?
>
>
> HTH
>
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn * 
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> *
>
>
>
> http://talebzadehmich.wordpress.com
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage 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 1 August 2016 at 07:04, Sri  wrote:
>
>> Hi ,
>>
>> Just wondering how spark SQL works behind the scenes does it not convert
>> SQL to some Scala RDD ? Or Scala ?
>>
>> How to write below SQL in Scala or Scala RDD
>>
>> SELECT DATE,balance,
>>
>> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>>
>> AND
>>
>> CURRENT ROW) daily_balance
>>
>> FROM  table
>>
>>
>> Thanks
>> Sri
>> Sent from my iPhone
>>
>> On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
>>
>> Hi,
>>
>> Impossible - see
>>
>> http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr]
>> .
>>
>> I tried to show you why you ended up with "non-empty iterator" after
>> println. You should really start with
>> http://www.scala-lang.org/documentation/
>>
>> Pozdrawiam,
>> Jacek Laskowski
>> 
>> https://medium.com/@jaceklaskowski/
>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>> Follow me at https://twitter.com/jaceklaskowski
>>
>>
>> On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
>>  wrote:
>>
>> Tuple
>>
>>
>> [Lscala.Tuple2;@65e4cb84
>>
>>
>> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>>
>>
>> Hi,
>>
>>
>> What's the result type of sliding(2,1)?
>>
>>
>> Pozdrawiam,
>>
>> Jacek Laskowski
>>
>> 
>>
>> https://medium.com/@jaceklaskowski/
>>
>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>
>> Follow me at https://twitter.com/jaceklaskowski
>>
>>
>>
>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>
>>  wrote:
>>
>> tried this no luck, wht is non-empty iterator here ?
>>
>>
>> OP:-
>>
>> (-987,non-empty iterator)
>>
>> (-987,non-empty iterator)
>>
>> (-987,non-empty iterator)
>>
>> (-987,non-empty iterator)
>>
>> (-987,non-empty iterator)
>>
>>
>>
>> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>
>>  .map(x => x._2.split("\\~"))
>>
>>  .map(x => (x(0),x(2)))
>>
>>.map { case (key,value) =>
>>
>> (key,value.toArray.toSeq.sliding(2,1).map(x
>>
>> => x.sum/x.size))}.foreach(println)
>>
>>
>>
>> On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>>
>>  wrote:
>>
>>
>> Hi All,
>>
>>
>> I managed to write using sliding

Re: sql to spark scala rdd

2016-08-01 Thread Sri

Hi ,

I solved it using spark SQL which uses similar window functions mentioned below 
, for my own knowledge I am trying to solve using Scala RDD which I am unable 
to.
What function in Scala supports window function like SQL unbounded preceding 
and current row ? Is it sliding ?


Thanks
Sri

Sent from my iPhone

> On 31 Jul 2016, at 23:16, Mich Talebzadeh  wrote:
> 
> hi
> 
> You mentioned:
> 
> I already solved it using DF and spark sql ...
> 
> Are you referring to this code which is a classic analytics:
> 
> 
> SELECT DATE,balance,
> 
>  SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>  AND
>  CURRENT ROW) daily_balance
>  FROM  table
> 
> So how did you solve it using DF in the first place?
> 
> 
> HTH
> 
> 
> Dr Mich Talebzadeh
>  
> LinkedIn  
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>  
> http://talebzadehmich.wordpress.com
> 
> Disclaimer: Use it at your own risk. Any and all responsibility for any loss, 
> damage 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 1 August 2016 at 07:04, Sri  wrote:
>> Hi ,
>> 
>> Just wondering how spark SQL works behind the scenes does it not convert SQL 
>> to some Scala RDD ? Or Scala ?
>> 
>> How to write below SQL in Scala or Scala RDD
>> 
>> SELECT DATE,balance,
>> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>> AND
>> CURRENT ROW) daily_balance
>> FROM  table
>> 
>> Thanks
>> Sri
>> Sent from my iPhone
>> 
>>> On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
>>> 
>>> Hi,
>>> 
>>> Impossible - see
>>> http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr].
>>> 
>>> I tried to show you why you ended up with "non-empty iterator" after
>>> println. You should really start with
>>> http://www.scala-lang.org/documentation/
>>> 
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>> 
>>> 
>>> On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
>>>  wrote:
 Tuple
 
 [Lscala.Tuple2;@65e4cb84
 
> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
> 
> Hi,
> 
> What's the result type of sliding(2,1)?
> 
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
> 
> 
> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>  wrote:
>> tried this no luck, wht is non-empty iterator here ?
>> 
>> OP:-
>> (-987,non-empty iterator)
>> (-987,non-empty iterator)
>> (-987,non-empty iterator)
>> (-987,non-empty iterator)
>> (-987,non-empty iterator)
>> 
>> 
>> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>  .map(x => x._2.split("\\~"))
>>  .map(x => (x(0),x(2)))
>>.map { case (key,value) =>
>> (key,value.toArray.toSeq.sliding(2,1).map(x
>> => x.sum/x.size))}.foreach(println)
>> 
>> 
>> On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>>  wrote:
>>> 
>>> Hi All,
>>> 
>>> I managed to write using sliding function but can it get key as well in
>>> my
>>> output ?
>>> 
>>> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>>  .map(x => x._2.split("\\~"))
>>>  .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>>> (x,x.size)).foreach(println)
>>> 
>>> 
>>> at the moment my output:-
>>> 
>>> 75.0
>>> -25.0
>>> 50.0
>>> -50.0
>>> -100.0
>>> 
>>> I want with key how to get moving average output based on key ?
>>> 
>>> 
>>> 987,75.0
>>> 987,-25
>>> 987,50.0
>>> 
>>> Thanks
>>> Sri
>>> 
>>> 
>>> 
>>> 
>>> 
>>> 
>>> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>>>  wrote:
 
 for knowledge just wondering how to write it up in scala or spark RDD.
 
 Thanks
 Sri
 
 On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
 wrote:
> 
> Why?
> 
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0

Re: sql to spark scala rdd

2016-08-01 Thread Mich Talebzadeh

hi

You mentioned:

I already solved it using DF and spark sql ...

Are you referring to this code which is a classic analytics:

SELECT DATE,balance,
 SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING

 AND

 CURRENT ROW) daily_balance

 FROM  table


So how did you solve it using DF in the first place?


HTH


Dr Mich Talebzadeh



LinkedIn * 
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
*



http://talebzadehmich.wordpress.com


*Disclaimer:* Use it at your own risk. Any and all responsibility for any
loss, damage 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 1 August 2016 at 07:04, Sri  wrote:

> Hi ,
>
> Just wondering how spark SQL works behind the scenes does it not convert
> SQL to some Scala RDD ? Or Scala ?
>
> How to write below SQL in Scala or Scala RDD
>
> SELECT DATE,balance,
>
> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>
> AND
>
> CURRENT ROW) daily_balance
>
> FROM  table
>
>
> Thanks
> Sri
> Sent from my iPhone
>
> On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
>
> Hi,
>
> Impossible - see
>
> http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr]
> .
>
> I tried to show you why you ended up with "non-empty iterator" after
> println. You should really start with
> http://www.scala-lang.org/documentation/
>
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
>
>
> On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
>  wrote:
>
> Tuple
>
>
> [Lscala.Tuple2;@65e4cb84
>
>
> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>
>
> Hi,
>
>
> What's the result type of sliding(2,1)?
>
>
> Pozdrawiam,
>
> Jacek Laskowski
>
> 
>
> https://medium.com/@jaceklaskowski/
>
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>
> Follow me at https://twitter.com/jaceklaskowski
>
>
>
> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>
>  wrote:
>
> tried this no luck, wht is non-empty iterator here ?
>
>
> OP:-
>
> (-987,non-empty iterator)
>
> (-987,non-empty iterator)
>
> (-987,non-empty iterator)
>
> (-987,non-empty iterator)
>
> (-987,non-empty iterator)
>
>
>
> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>
>  .map(x => x._2.split("\\~"))
>
>  .map(x => (x(0),x(2)))
>
>.map { case (key,value) =>
>
> (key,value.toArray.toSeq.sliding(2,1).map(x
>
> => x.sum/x.size))}.foreach(println)
>
>
>
> On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>
>  wrote:
>
>
> Hi All,
>
>
> I managed to write using sliding function but can it get key as well in
>
> my
>
> output ?
>
>
> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>
>  .map(x => x._2.split("\\~"))
>
>  .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>
> (x,x.size)).foreach(println)
>
>
>
> at the moment my output:-
>
>
> 75.0
>
> -25.0
>
> 50.0
>
> -50.0
>
> -100.0
>
>
> I want with key how to get moving average output based on key ?
>
>
>
> 987,75.0
>
> 987,-25
>
> 987,50.0
>
>
> Thanks
>
> Sri
>
>
>
>
>
>
>
> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>
>  wrote:
>
>
> for knowledge just wondering how to write it up in scala or spark RDD.
>
>
> Thanks
>
> Sri
>
>
> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>
> wrote:
>
>
> Why?
>
>
> Pozdrawiam,
>
> Jacek Laskowski
>
> 
>
> https://medium.com/@jaceklaskowski/
>
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>
> Follow me at https://twitter.com/jaceklaskowski
>
>
>
> On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>
>  wrote:
>
> Hi All,
>
>
> I managed to write business requirement in spark-sql and hive I am
>
> still
>
> learning scala how this below sql be written using spark RDD not
>
> spark
>
> data
>
> frames.
>
>
> SELECT DATE,balance,
>
> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>
> AND
>
> CURRENT ROW) daily_balance
>
> FROM  table
>
>
>
>
>
>
> --
>
> View this message in context:
>
>
>
> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>
> Sent from the Apache Spark User List mailing list archive at
>
> Nabble.com .
>
>
>
> -
>
> To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>
>
>
>
>
>
> --
>
> Thanks & Regards
>
> Sri Tummala
>
>
>
>
>
>

Re: sql to spark scala rdd

2016-08-01 Thread Sri

Hi ,

Just wondering how spark SQL works behind the scenes does it not convert SQL to 
some Scala RDD ? Or Scala ?

How to write below SQL in Scala or Scala RDD

 SELECT DATE,balance,
 SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
 AND
 CURRENT ROW) daily_balance
 FROM  table

Thanks
Sri
Sent from my iPhone

> On 31 Jul 2016, at 13:21, Jacek Laskowski  wrote:
> 
> Hi,
> 
> Impossible - see
> http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr].
> 
> I tried to show you why you ended up with "non-empty iterator" after
> println. You should really start with
> http://www.scala-lang.org/documentation/
> 
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
> 
> 
> On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
>  wrote:
>> Tuple
>> 
>> [Lscala.Tuple2;@65e4cb84
>> 
>>> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>>> 
>>> Hi,
>>> 
>>> What's the result type of sliding(2,1)?
>>> 
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>> 
>>> 
>>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>>  wrote:
 tried this no luck, wht is non-empty iterator here ?
 
 OP:-
 (-987,non-empty iterator)
 (-987,non-empty iterator)
 (-987,non-empty iterator)
 (-987,non-empty iterator)
 (-987,non-empty iterator)
 
 
 sc.textFile(file).keyBy(x => x.split("\\~") (0))
  .map(x => x._2.split("\\~"))
  .map(x => (x(0),x(2)))
.map { case (key,value) =>
 (key,value.toArray.toSeq.sliding(2,1).map(x
 => x.sum/x.size))}.foreach(println)
 
 
 On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
  wrote:
> 
> Hi All,
> 
> I managed to write using sliding function but can it get key as well in
> my
> output ?
> 
> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>  .map(x => x._2.split("\\~"))
>  .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
> (x,x.size)).foreach(println)
> 
> 
> at the moment my output:-
> 
> 75.0
> -25.0
> 50.0
> -50.0
> -100.0
> 
> I want with key how to get moving average output based on key ?
> 
> 
> 987,75.0
> 987,-25
> 987,50.0
> 
> Thanks
> Sri
> 
> 
> 
> 
> 
> 
> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>  wrote:
>> 
>> for knowledge just wondering how to write it up in scala or spark RDD.
>> 
>> Thanks
>> Sri
>> 
>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>> wrote:
>>> 
>>> Why?
>>> 
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>> 
>>> 
>>> On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>>  wrote:
 Hi All,
 
 I managed to write business requirement in spark-sql and hive I am
 still
 learning scala how this below sql be written using spark RDD not
 spark
 data
 frames.
 
 SELECT DATE,balance,
 SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
 AND
 CURRENT ROW) daily_balance
 FROM  table
 
 
 
 
 
 --
 View this message in context:
 
 http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
 Sent from the Apache Spark User List mailing list archive at
 Nabble.com.
 
 
 -
 To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>> 
>> 
>> 
>> 
>> --
>> Thanks & Regards
>> Sri Tummala
> 
> 
> 
> --
> Thanks & Regards
> Sri Tummala
 
 
 
 --
 Thanks & Regards
 Sri Tummala
>> 
>> 
>> 
>> 
>> --
>> Thanks & Regards
>> Sri Tummala
>>

Re: sql to spark scala rdd

2016-07-31 Thread Jacek Laskowski

Hi,

Impossible - see
http://www.scala-lang.org/api/current/index.html#scala.collection.Seq@sliding(size:Int,step:Int):Iterator[Repr].

I tried to show you why you ended up with "non-empty iterator" after
println. You should really start with
http://www.scala-lang.org/documentation/

Pozdrawiam,
Jacek Laskowski

https://medium.com/@jaceklaskowski/
Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
Follow me at https://twitter.com/jaceklaskowski


On Sun, Jul 31, 2016 at 8:49 PM, sri hari kali charan Tummala
 wrote:
> Tuple
>
> [Lscala.Tuple2;@65e4cb84
>
> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>>
>> Hi,
>>
>> What's the result type of sliding(2,1)?
>>
>> Pozdrawiam,
>> Jacek Laskowski
>> 
>> https://medium.com/@jaceklaskowski/
>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>> Follow me at https://twitter.com/jaceklaskowski
>>
>>
>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>  wrote:
>> > tried this no luck, wht is non-empty iterator here ?
>> >
>> > OP:-
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> >
>> >
>> > sc.textFile(file).keyBy(x => x.split("\\~") (0))
>> >   .map(x => x._2.split("\\~"))
>> >   .map(x => (x(0),x(2)))
>> > .map { case (key,value) =>
>> > (key,value.toArray.toSeq.sliding(2,1).map(x
>> > => x.sum/x.size))}.foreach(println)
>> >
>> >
>> > On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>> >  wrote:
>> >>
>> >> Hi All,
>> >>
>> >> I managed to write using sliding function but can it get key as well in
>> >> my
>> >> output ?
>> >>
>> >> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>> >>   .map(x => x._2.split("\\~"))
>> >>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>> >> (x,x.size)).foreach(println)
>> >>
>> >>
>> >> at the moment my output:-
>> >>
>> >> 75.0
>> >> -25.0
>> >> 50.0
>> >> -50.0
>> >> -100.0
>> >>
>> >> I want with key how to get moving average output based on key ?
>> >>
>> >>
>> >> 987,75.0
>> >> 987,-25
>> >> 987,50.0
>> >>
>> >> Thanks
>> >> Sri
>> >>
>> >>
>> >>
>> >>
>> >>
>> >>
>> >> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>> >>  wrote:
>> >>>
>> >>> for knowledge just wondering how to write it up in scala or spark RDD.
>> >>>
>> >>> Thanks
>> >>> Sri
>> >>>
>> >>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>> >>> wrote:
>> 
>>  Why?
>> 
>>  Pozdrawiam,
>>  Jacek Laskowski
>>  
>>  https://medium.com/@jaceklaskowski/
>>  Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>  Follow me at https://twitter.com/jaceklaskowski
>> 
>> 
>>  On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>   wrote:
>>  > Hi All,
>>  >
>>  > I managed to write business requirement in spark-sql and hive I am
>>  > still
>>  > learning scala how this below sql be written using spark RDD not
>>  > spark
>>  > data
>>  > frames.
>>  >
>>  > SELECT DATE,balance,
>>  > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>>  > AND
>>  > CURRENT ROW) daily_balance
>>  > FROM  table
>>  >
>>  >
>>  >
>>  >
>>  >
>>  > --
>>  > View this message in context:
>>  >
>>  > http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>>  > Sent from the Apache Spark User List mailing list archive at
>>  > Nabble.com.
>>  >
>>  >
>>  > -
>>  > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>>  >
>> >>>
>> >>>
>> >>>
>> >>>
>> >>> --
>> >>> Thanks & Regards
>> >>> Sri Tummala
>> >>>
>> >>
>> >>
>> >>
>> >> --
>> >> Thanks & Regards
>> >> Sri Tummala
>> >>
>> >
>> >
>> >
>> > --
>> > Thanks & Regards
>> > Sri Tummala
>> >
>
>
>
>
> --
> Thanks & Regards
> Sri Tummala
>

-
To unsubscribe e-mail: user-unsubscr...@spark.apache.org

Re: sql to spark scala rdd

2016-07-31 Thread sri hari kali charan Tummala

val test=sc.textFile(file).keyBy(x => x.split("\\~") (0))
  .map(x => x._2.split("\\~"))
  .map(x => ((x(0),x(1),x(2
  .map{case (account,datevalue,amount) =>
((account,datevalue),(amount.toDouble))}.mapValues(x =>
x).toArray.sliding(2,1).map(x => (x(0)._1,x(1)._2,(x.foldLeft(0.0)(_ +
_._2/x.size)),x.foldLeft(0.0)(_ + _._2))).foreach(println)


On Sun, Jul 31, 2016 at 12:15 PM, sri hari kali charan Tummala <
kali.tumm...@gmail.com> wrote:

> Hi All,
>
> I already solved it using DF and spark sql I was wondering how to solve in
> scala rdd, I just got the answer need to check my results compared to spark
> sql thanks all for your time.
>
> I am trying to solve moving average using scala RDD group by key.
>
>
> input:-
> -987~20150728~100
> -987~20150729~50
> -987~20150730~-100
> -987~20150804~200
> -987~20150807~-300
> -987~20150916~100
>
>
> val test=sc.textFile(file).keyBy(x => x.split("\\~") (0))
>   .map(x => x._2.split("\\~"))
>   .map(x => ((x(0),x(1),x(2
>   .map{case (account,datevalue,amount) => 
> ((account,datevalue),(amount.toDouble))}.mapValues(x => 
> x).toArray.sliding(2,1).map(x => (x(0)._1,x(1)._2,(x.foldLeft(0.0)(_ + 
> _._2/x.size)),x.foldLeft(0.0)(_ + _._2))).foreach(println)
>
> Op:-
>
> accountkey,date,balance_of_account, daily_average, sum_base_on_window
>
> ((-987,20150728),50.0,75.0,150.0)
> ((-987,20150729),-100.0,-25.0,-50.0)
> ((-987,20150730),200.0,50.0,100.0)
> ((-987,20150804),-300.0,-50.0,-100.0)
> ((-987,20150807),100.0,-100.0,-200.0)
>
>
> below book is written for Hadoop Mapreduce the book has solution for
> moving average but its in Java.
>
>
> https://www.safaribooksonline.com/library/view/data-algorithms/9781491906170/ch06.html
>
>
> Sql:-
>
>
> SELECT DATE,balance,
> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
> CURRENT ROW) daily_balance
> FROM  table
>
> Thanks
> Sri
>
>
>
> On Sun, Jul 31, 2016 at 11:54 AM, Mich Talebzadeh <
> mich.talebza...@gmail.com> wrote:
>
>> Check also this
>> 
>>
>> HTH
>>
>> Dr Mich Talebzadeh
>>
>>
>>
>> LinkedIn * 
>> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>> *
>>
>>
>>
>> http://talebzadehmich.wordpress.com
>>
>>
>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>> any loss, damage 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 31 July 2016 at 19:49, sri hari kali charan Tummala <
>> kali.tumm...@gmail.com> wrote:
>>
>>> Tuple
>>>
>>> [Lscala.Tuple2;@65e4cb84
>>>
>>> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski 
>>> wrote:
>>>
 Hi,

 What's the result type of sliding(2,1)?

 Pozdrawiam,
 Jacek Laskowski
 
 https://medium.com/@jaceklaskowski/
 Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
 Follow me at https://twitter.com/jaceklaskowski


 On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
  wrote:
 > tried this no luck, wht is non-empty iterator here ?
 >
 > OP:-
 > (-987,non-empty iterator)
 > (-987,non-empty iterator)
 > (-987,non-empty iterator)
 > (-987,non-empty iterator)
 > (-987,non-empty iterator)
 >
 >
 > sc.textFile(file).keyBy(x => x.split("\\~") (0))
 >   .map(x => x._2.split("\\~"))
 >   .map(x => (x(0),x(2)))
 > .map { case (key,value) =>
 (key,value.toArray.toSeq.sliding(2,1).map(x
 > => x.sum/x.size))}.foreach(println)
 >
 >
 > On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
 >  wrote:
 >>
 >> Hi All,
 >>
 >> I managed to write using sliding function but can it get key as well
 in my
 >> output ?
 >>
 >> sc.textFile(file).keyBy(x => x.split("\\~") (0))
 >>   .map(x => x._2.split("\\~"))
 >>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
 >> (x,x.size)).foreach(println)
 >>
 >>
 >> at the moment my output:-
 >>
 >> 75.0
 >> -25.0
 >> 50.0
 >> -50.0
 >> -100.0
 >>
 >> I want with key how to get moving average output based on key ?
 >>
 >>
 >> 987,75.0
 >> 987,-25
 >> 987,50.0
 >>
 >> Thanks
 >> Sri
 >>
 >>
 >>
 >>
 >>
 >>
 >> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
 >>  wrote:
 >>>
 >>> for knowledge just wondering how to write it up in scala or spark
 RDD.
 >>>
 >>> Thanks
 >>> Sri
 >>>
 >>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski

Re: sql to spark scala rdd

2016-07-31 Thread sri hari kali charan Tummala

Hi All,

I already solved it using DF and spark sql I was wondering how to solve in
scala rdd, I just got the answer need to check my results compared to spark
sql thanks all for your time.

I am trying to solve moving average using scala RDD group by key.


input:-
-987~20150728~100
-987~20150729~50
-987~20150730~-100
-987~20150804~200
-987~20150807~-300
-987~20150916~100


val test=sc.textFile(file).keyBy(x => x.split("\\~") (0))
  .map(x => x._2.split("\\~"))
  .map(x => ((x(0),x(1),x(2
  .map{case (account,datevalue,amount) =>
((account,datevalue),(amount.toDouble))}.mapValues(x =>
x).toArray.sliding(2,1).map(x => (x(0)._1,x(1)._2,(x.foldLeft(0.0)(_ +
_._2/x.size)),x.foldLeft(0.0)(_ + _._2))).foreach(println)

Op:-

accountkey,date,balance_of_account, daily_average, sum_base_on_window

((-987,20150728),50.0,75.0,150.0)
((-987,20150729),-100.0,-25.0,-50.0)
((-987,20150730),200.0,50.0,100.0)
((-987,20150804),-300.0,-50.0,-100.0)
((-987,20150807),100.0,-100.0,-200.0)


below book is written for Hadoop Mapreduce the book has solution for moving
average but its in Java.

https://www.safaribooksonline.com/library/view/data-algorithms/9781491906170/ch06.html


Sql:-


SELECT DATE,balance,
SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
CURRENT ROW) daily_balance
FROM  table

Thanks
Sri



On Sun, Jul 31, 2016 at 11:54 AM, Mich Talebzadeh  wrote:

> Check also this
> 
>
> HTH
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn * 
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> *
>
>
>
> http://talebzadehmich.wordpress.com
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage 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 31 July 2016 at 19:49, sri hari kali charan Tummala <
> kali.tumm...@gmail.com> wrote:
>
>> Tuple
>>
>> [Lscala.Tuple2;@65e4cb84
>>
>> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>>
>>> Hi,
>>>
>>> What's the result type of sliding(2,1)?
>>>
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>>
>>>
>>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>>  wrote:
>>> > tried this no luck, wht is non-empty iterator here ?
>>> >
>>> > OP:-
>>> > (-987,non-empty iterator)
>>> > (-987,non-empty iterator)
>>> > (-987,non-empty iterator)
>>> > (-987,non-empty iterator)
>>> > (-987,non-empty iterator)
>>> >
>>> >
>>> > sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>> >   .map(x => x._2.split("\\~"))
>>> >   .map(x => (x(0),x(2)))
>>> > .map { case (key,value) =>
>>> (key,value.toArray.toSeq.sliding(2,1).map(x
>>> > => x.sum/x.size))}.foreach(println)
>>> >
>>> >
>>> > On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>>> >  wrote:
>>> >>
>>> >> Hi All,
>>> >>
>>> >> I managed to write using sliding function but can it get key as well
>>> in my
>>> >> output ?
>>> >>
>>> >> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>> >>   .map(x => x._2.split("\\~"))
>>> >>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>>> >> (x,x.size)).foreach(println)
>>> >>
>>> >>
>>> >> at the moment my output:-
>>> >>
>>> >> 75.0
>>> >> -25.0
>>> >> 50.0
>>> >> -50.0
>>> >> -100.0
>>> >>
>>> >> I want with key how to get moving average output based on key ?
>>> >>
>>> >>
>>> >> 987,75.0
>>> >> 987,-25
>>> >> 987,50.0
>>> >>
>>> >> Thanks
>>> >> Sri
>>> >>
>>> >>
>>> >>
>>> >>
>>> >>
>>> >>
>>> >> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>>> >>  wrote:
>>> >>>
>>> >>> for knowledge just wondering how to write it up in scala or spark
>>> RDD.
>>> >>>
>>> >>> Thanks
>>> >>> Sri
>>> >>>
>>> >>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>>> >>> wrote:
>>> 
>>>  Why?
>>> 
>>>  Pozdrawiam,
>>>  Jacek Laskowski
>>>  
>>>  https://medium.com/@jaceklaskowski/
>>>  Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>>  Follow me at https://twitter.com/jaceklaskowski
>>> 
>>> 
>>>  On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>>   wrote:
>>>  > Hi All,
>>>  >
>>>  > I managed to write business requirement in spark-sql and hive I am
>>>  > still
>>>  > learning scala how this below sql be written using spark RDD not
>>> spark
>>>  > data
>>>  > frames.

Re: sql to spark scala rdd

2016-07-31 Thread Mich Talebzadeh

Check also this


HTH

Dr Mich Talebzadeh



LinkedIn * 
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
*



http://talebzadehmich.wordpress.com


*Disclaimer:* Use it at your own risk. Any and all responsibility for any
loss, damage 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 31 July 2016 at 19:49, sri hari kali charan Tummala <
kali.tumm...@gmail.com> wrote:

> Tuple
>
> [Lscala.Tuple2;@65e4cb84
>
> On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:
>
>> Hi,
>>
>> What's the result type of sliding(2,1)?
>>
>> Pozdrawiam,
>> Jacek Laskowski
>> 
>> https://medium.com/@jaceklaskowski/
>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>> Follow me at https://twitter.com/jaceklaskowski
>>
>>
>> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>>  wrote:
>> > tried this no luck, wht is non-empty iterator here ?
>> >
>> > OP:-
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> > (-987,non-empty iterator)
>> >
>> >
>> > sc.textFile(file).keyBy(x => x.split("\\~") (0))
>> >   .map(x => x._2.split("\\~"))
>> >   .map(x => (x(0),x(2)))
>> > .map { case (key,value) =>
>> (key,value.toArray.toSeq.sliding(2,1).map(x
>> > => x.sum/x.size))}.foreach(println)
>> >
>> >
>> > On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>> >  wrote:
>> >>
>> >> Hi All,
>> >>
>> >> I managed to write using sliding function but can it get key as well
>> in my
>> >> output ?
>> >>
>> >> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>> >>   .map(x => x._2.split("\\~"))
>> >>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>> >> (x,x.size)).foreach(println)
>> >>
>> >>
>> >> at the moment my output:-
>> >>
>> >> 75.0
>> >> -25.0
>> >> 50.0
>> >> -50.0
>> >> -100.0
>> >>
>> >> I want with key how to get moving average output based on key ?
>> >>
>> >>
>> >> 987,75.0
>> >> 987,-25
>> >> 987,50.0
>> >>
>> >> Thanks
>> >> Sri
>> >>
>> >>
>> >>
>> >>
>> >>
>> >>
>> >> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>> >>  wrote:
>> >>>
>> >>> for knowledge just wondering how to write it up in scala or spark RDD.
>> >>>
>> >>> Thanks
>> >>> Sri
>> >>>
>> >>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>> >>> wrote:
>> 
>>  Why?
>> 
>>  Pozdrawiam,
>>  Jacek Laskowski
>>  
>>  https://medium.com/@jaceklaskowski/
>>  Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>  Follow me at https://twitter.com/jaceklaskowski
>> 
>> 
>>  On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>   wrote:
>>  > Hi All,
>>  >
>>  > I managed to write business requirement in spark-sql and hive I am
>>  > still
>>  > learning scala how this below sql be written using spark RDD not
>> spark
>>  > data
>>  > frames.
>>  >
>>  > SELECT DATE,balance,
>>  > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
>> AND
>>  > CURRENT ROW) daily_balance
>>  > FROM  table
>>  >
>>  >
>>  >
>>  >
>>  >
>>  > --
>>  > View this message in context:
>>  >
>> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>>  > Sent from the Apache Spark User List mailing list archive at
>>  > Nabble.com.
>>  >
>>  >
>> -
>>  > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>>  >
>> >>>
>> >>>
>> >>>
>> >>>
>> >>> --
>> >>> Thanks & Regards
>> >>> Sri Tummala
>> >>>
>> >>
>> >>
>> >>
>> >> --
>> >> Thanks & Regards
>> >> Sri Tummala
>> >>
>> >
>> >
>> >
>> > --
>> > Thanks & Regards
>> > Sri Tummala
>> >
>>
>
>
>
> --
> Thanks & Regards
> Sri Tummala
>
>

Re: sql to spark scala rdd

2016-07-31 Thread sri hari kali charan Tummala

Tuple

[Lscala.Tuple2;@65e4cb84

On Sun, Jul 31, 2016 at 1:00 AM, Jacek Laskowski  wrote:

> Hi,
>
> What's the result type of sliding(2,1)?
>
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
>
>
> On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
>  wrote:
> > tried this no luck, wht is non-empty iterator here ?
> >
> > OP:-
> > (-987,non-empty iterator)
> > (-987,non-empty iterator)
> > (-987,non-empty iterator)
> > (-987,non-empty iterator)
> > (-987,non-empty iterator)
> >
> >
> > sc.textFile(file).keyBy(x => x.split("\\~") (0))
> >   .map(x => x._2.split("\\~"))
> >   .map(x => (x(0),x(2)))
> > .map { case (key,value) =>
> (key,value.toArray.toSeq.sliding(2,1).map(x
> > => x.sum/x.size))}.foreach(println)
> >
> >
> > On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
> >  wrote:
> >>
> >> Hi All,
> >>
> >> I managed to write using sliding function but can it get key as well in
> my
> >> output ?
> >>
> >> sc.textFile(file).keyBy(x => x.split("\\~") (0))
> >>   .map(x => x._2.split("\\~"))
> >>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
> >> (x,x.size)).foreach(println)
> >>
> >>
> >> at the moment my output:-
> >>
> >> 75.0
> >> -25.0
> >> 50.0
> >> -50.0
> >> -100.0
> >>
> >> I want with key how to get moving average output based on key ?
> >>
> >>
> >> 987,75.0
> >> 987,-25
> >> 987,50.0
> >>
> >> Thanks
> >> Sri
> >>
> >>
> >>
> >>
> >>
> >>
> >> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
> >>  wrote:
> >>>
> >>> for knowledge just wondering how to write it up in scala or spark RDD.
> >>>
> >>> Thanks
> >>> Sri
> >>>
> >>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
> >>> wrote:
> 
>  Why?
> 
>  Pozdrawiam,
>  Jacek Laskowski
>  
>  https://medium.com/@jaceklaskowski/
>  Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>  Follow me at https://twitter.com/jaceklaskowski
> 
> 
>  On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>   wrote:
>  > Hi All,
>  >
>  > I managed to write business requirement in spark-sql and hive I am
>  > still
>  > learning scala how this below sql be written using spark RDD not
> spark
>  > data
>  > frames.
>  >
>  > SELECT DATE,balance,
>  > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING
> AND
>  > CURRENT ROW) daily_balance
>  > FROM  table
>  >
>  >
>  >
>  >
>  >
>  > --
>  > View this message in context:
>  >
> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>  > Sent from the Apache Spark User List mailing list archive at
>  > Nabble.com.
>  >
>  >
> -
>  > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>  >
> >>>
> >>>
> >>>
> >>>
> >>> --
> >>> Thanks & Regards
> >>> Sri Tummala
> >>>
> >>
> >>
> >>
> >> --
> >> Thanks & Regards
> >> Sri Tummala
> >>
> >
> >
> >
> > --
> > Thanks & Regards
> > Sri Tummala
> >
>



-- 
Thanks & Regards
Sri Tummala

Re: sql to spark scala rdd

2016-07-31 Thread Jacek Laskowski

Hi,

What's the result type of sliding(2,1)?

Pozdrawiam,
Jacek Laskowski

https://medium.com/@jaceklaskowski/
Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
Follow me at https://twitter.com/jaceklaskowski


On Sun, Jul 31, 2016 at 9:23 AM, sri hari kali charan Tummala
 wrote:
> tried this no luck, wht is non-empty iterator here ?
>
> OP:-
> (-987,non-empty iterator)
> (-987,non-empty iterator)
> (-987,non-empty iterator)
> (-987,non-empty iterator)
> (-987,non-empty iterator)
>
>
> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>   .map(x => x._2.split("\\~"))
>   .map(x => (x(0),x(2)))
> .map { case (key,value) => (key,value.toArray.toSeq.sliding(2,1).map(x
> => x.sum/x.size))}.foreach(println)
>
>
> On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala
>  wrote:
>>
>> Hi All,
>>
>> I managed to write using sliding function but can it get key as well in my
>> output ?
>>
>> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>>   .map(x => x._2.split("\\~"))
>>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
>> (x,x.size)).foreach(println)
>>
>>
>> at the moment my output:-
>>
>> 75.0
>> -25.0
>> 50.0
>> -50.0
>> -100.0
>>
>> I want with key how to get moving average output based on key ?
>>
>>
>> 987,75.0
>> 987,-25
>> 987,50.0
>>
>> Thanks
>> Sri
>>
>>
>>
>>
>>
>>
>> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala
>>  wrote:
>>>
>>> for knowledge just wondering how to write it up in scala or spark RDD.
>>>
>>> Thanks
>>> Sri
>>>
>>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>>> wrote:

 Why?

 Pozdrawiam,
 Jacek Laskowski
 
 https://medium.com/@jaceklaskowski/
 Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
 Follow me at https://twitter.com/jaceklaskowski


 On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
  wrote:
 > Hi All,
 >
 > I managed to write business requirement in spark-sql and hive I am
 > still
 > learning scala how this below sql be written using spark RDD not spark
 > data
 > frames.
 >
 > SELECT DATE,balance,
 > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
 > CURRENT ROW) daily_balance
 > FROM  table
 >
 >
 >
 >
 >
 > --
 > View this message in context:
 > http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
 > Sent from the Apache Spark User List mailing list archive at
 > Nabble.com.
 >
 > -
 > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
 >
>>>
>>>
>>>
>>>
>>> --
>>> Thanks & Regards
>>> Sri Tummala
>>>
>>
>>
>>
>> --
>> Thanks & Regards
>> Sri Tummala
>>
>
>
>
> --
> Thanks & Regards
> Sri Tummala
>

-
To unsubscribe e-mail: user-unsubscr...@spark.apache.org

Re: sql to spark scala rdd

2016-07-31 Thread sri hari kali charan Tummala

tried this no luck, wht is non-empty iterator here ?

OP:-
(-987,non-empty iterator)
(-987,non-empty iterator)
(-987,non-empty iterator)
(-987,non-empty iterator)
(-987,non-empty iterator)


sc.textFile(file).keyBy(x => x.split("\\~") (0))
  .map(x => x._2.split("\\~"))
  .map(x => (x(0),x(2)))
.map { case (key,value) =>
(key,value.toArray.toSeq.sliding(2,1).map(x =>
x.sum/x.size))}.foreach(println)


On Sun, Jul 31, 2016 at 12:03 AM, sri hari kali charan Tummala <
kali.tumm...@gmail.com> wrote:

> Hi All,
>
> I managed to write using sliding function but can it get key as well in my
> output ?
>
> sc.textFile(file).keyBy(x => x.split("\\~") (0))
>   .map(x => x._2.split("\\~"))
>   .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x => 
> (x,x.size)).foreach(println)
>
>
> at the moment my output:-
>
> 75.0
> -25.0
> 50.0
> -50.0
> -100.0
>
> I want with key how to get moving average output based on key ?
>
>
> 987,75.0
> 987,-25
> 987,50.0
>
> Thanks
> Sri
>
>
>
>
>
>
> On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala <
> kali.tumm...@gmail.com> wrote:
>
>> for knowledge just wondering how to write it up in scala or spark RDD.
>>
>> Thanks
>> Sri
>>
>> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski 
>> wrote:
>>
>>> Why?
>>>
>>> Pozdrawiam,
>>> Jacek Laskowski
>>> 
>>> https://medium.com/@jaceklaskowski/
>>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>>> Follow me at https://twitter.com/jaceklaskowski
>>>
>>>
>>> On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>>  wrote:
>>> > Hi All,
>>> >
>>> > I managed to write business requirement in spark-sql and hive I am
>>> still
>>> > learning scala how this below sql be written using spark RDD not spark
>>> data
>>> > frames.
>>> >
>>> > SELECT DATE,balance,
>>> > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
>>> > CURRENT ROW) daily_balance
>>> > FROM  table
>>> >
>>> >
>>> >
>>> >
>>> >
>>> > --
>>> > View this message in context:
>>> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>>> > Sent from the Apache Spark User List mailing list archive at
>>> Nabble.com.
>>> >
>>> > -
>>> > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>>> >
>>>
>>
>>
>>
>> --
>> Thanks & Regards
>> Sri Tummala
>>
>>
>
>
> --
> Thanks & Regards
> Sri Tummala
>
>


-- 
Thanks & Regards
Sri Tummala

Re: sql to spark scala rdd

2016-07-31 Thread sri hari kali charan Tummala

Hi All,

I managed to write using sliding function but can it get key as well in my
output ?

sc.textFile(file).keyBy(x => x.split("\\~") (0))
  .map(x => x._2.split("\\~"))
  .map(x => (x(2).toDouble)).toArray().sliding(2,1).map(x =>
(x,x.size)).foreach(println)


at the moment my output:-

75.0
-25.0
50.0
-50.0
-100.0

I want with key how to get moving average output based on key ?


987,75.0
987,-25
987,50.0

Thanks
Sri






On Sat, Jul 30, 2016 at 11:40 AM, sri hari kali charan Tummala <
kali.tumm...@gmail.com> wrote:

> for knowledge just wondering how to write it up in scala or spark RDD.
>
> Thanks
> Sri
>
> On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski  wrote:
>
>> Why?
>>
>> Pozdrawiam,
>> Jacek Laskowski
>> 
>> https://medium.com/@jaceklaskowski/
>> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
>> Follow me at https://twitter.com/jaceklaskowski
>>
>>
>> On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>>  wrote:
>> > Hi All,
>> >
>> > I managed to write business requirement in spark-sql and hive I am still
>> > learning scala how this below sql be written using spark RDD not spark
>> data
>> > frames.
>> >
>> > SELECT DATE,balance,
>> > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
>> > CURRENT ROW) daily_balance
>> > FROM  table
>> >
>> >
>> >
>> >
>> >
>> > --
>> > View this message in context:
>> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
>> > Sent from the Apache Spark User List mailing list archive at Nabble.com.
>> >
>> > -
>> > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>> >
>>
>
>
>
> --
> Thanks & Regards
> Sri Tummala
>
>


-- 
Thanks & Regards
Sri Tummala

Re: sql to spark scala rdd

2016-07-30 Thread sri hari kali charan Tummala

for knowledge just wondering how to write it up in scala or spark RDD.

Thanks
Sri

On Sat, Jul 30, 2016 at 11:24 AM, Jacek Laskowski  wrote:

> Why?
>
> Pozdrawiam,
> Jacek Laskowski
> 
> https://medium.com/@jaceklaskowski/
> Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
> Follow me at https://twitter.com/jaceklaskowski
>
>
> On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
>  wrote:
> > Hi All,
> >
> > I managed to write business requirement in spark-sql and hive I am still
> > learning scala how this below sql be written using spark RDD not spark
> data
> > frames.
> >
> > SELECT DATE,balance,
> > SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
> > CURRENT ROW) daily_balance
> > FROM  table
> >
> >
> >
> >
> >
> > --
> > View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
> > Sent from the Apache Spark User List mailing list archive at Nabble.com.
> >
> > -
> > To unsubscribe e-mail: user-unsubscr...@spark.apache.org
> >
>



-- 
Thanks & Regards
Sri Tummala

Re: sql to spark scala rdd

2016-07-30 Thread Jacek Laskowski

Why?

Pozdrawiam,
Jacek Laskowski

https://medium.com/@jaceklaskowski/
Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
Follow me at https://twitter.com/jaceklaskowski


On Sat, Jul 30, 2016 at 4:42 AM, kali.tumm...@gmail.com
 wrote:
> Hi All,
>
> I managed to write business requirement in spark-sql and hive I am still
> learning scala how this below sql be written using spark RDD not spark data
> frames.
>
> SELECT DATE,balance,
> SUM(balance) OVER (ORDER BY DATE ROWS BETWEEN UNBOUNDED PRECEDING AND
> CURRENT ROW) daily_balance
> FROM  table
>
>
>
>
>
> --
> View this message in context: 
> http://apache-spark-user-list.1001560.n3.nabble.com/sql-to-spark-scala-rdd-tp27433.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
> -
> To unsubscribe e-mail: user-unsubscr...@spark.apache.org
>

-
To unsubscribe e-mail: user-unsubscr...@spark.apache.org

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Re: sql to spark scala rdd

Re: sql to spark scala rdd

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