Perfect, that's exactly what I was looking for.
Thank you!
On Mon, Dec 15, 2014 at 3:32 AM, Yanbo Liang <yanboha...@gmail.com> wrote:
>
> Hi Nathan,
>
> #1
>
> Spark SQL & DSL can satisfy your requirement. You can refer the following
> code snippet:
>
> jdata.select(Star(Node), 'seven.getField("mod"), 'eleven.getField("mod"))
>
> You need to import org.apache.spark.sql.catalyst.analysis.Star in advance.
>
> #2
>
> After you make the transform above, you do not need to make SchemaRDD
> manually.
> Because that jdata.select() return a SchemaRDD and you can operate on it
> directly.
>
> For example, the following code snippet will return a new SchemaRDD with
> longer Row:
>
> val t1 = jdata.select(Star(Node), 'seven.getField("mod") +
> 'eleven.getField("mod") as 'mod_sum)
>
> You can use t1.printSchema() to print the schema of this SchemaRDD and
> check whether it satisfy your requirements.
>
>
>
> 2014-12-13 0:00 GMT+08:00 Nathan Kronenfeld <nkronenf...@oculusinfo.com>:
>>
>> (1) I understand about immutability, that's why I said I wanted a new
>> SchemaRDD.
>> (2) I specfically asked for a non-SQL solution that takes a SchemaRDD,
>> and results in a new SchemaRDD with one new function.
>> (3) The DSL stuff is a big clue, but I can't find adequate documentation
>> for it
>>
>> What I'm looking for is something like:
>>
>> import org.apache.spark.sql._
>>
>>
>> val sqlc = new SQLContext(sc)
>> import sqlc._
>>
>>
>> val data = sc.parallelize(0 to 99).map(n =>
>> ("{\"seven\": {\"mod\": %d, \"times\": %d}, "+
>> "\"eleven\": {\"mod\": %d, \"times\": %d}}").format(n % 7, n * 7, n
>> % 11, n * 11))
>> val jdata = sqlc.jsonRDD(data)
>> jdata.registerTempTable("jdata")
>>
>>
>> val sqlVersion = sqlc.sql("SELECT *, (seven.mod + eleven.mod) AS modsum
>> FROM jdata")
>>
>>
>> This sqlVersion works fine, but if I try to do the same thing with a
>> programatic function, I'm missing a bunch of pieces:
>>
>> - I assume I'd need to start with something like:
>> jdata.select('*, 'seven.mod, 'eleven.mod)
>> and then get and process the last two elements. The problems are:
>> - I can't select '* - there seems no way to get the complete row
>> - I can't select 'seven.mod or 'eleven.mod - the symbol evaluation
>> seems only one deep.
>> - Assuming I could do that, I don't see a way to make the result into
>> a SchemaRDD. I assume I would have to do something like:
>> 1. take my row and value, and create a new, slightly longer row
>> 2. take my old schema, and create a new schema with one more field
>> at the end, named and typed appropriately
>> 3. combine the two into a SchemaRDD
>> I think I see how to do 3, but 1 and 2 elude me.
>>
>> Is there more complete documentation somewhere for the DSL portion?
>> Anyone have a clue about any of the above?
>>
>>
>>
>> On Fri, Dec 12, 2014 at 6:01 AM, Yanbo Liang <yanboha...@gmail.com>
>> wrote:
>>
>>> RDD is immutable so you can not modify it.
>>> If you want to modify some value or schema in RDD, using map to
>>> generate a new RDD.
>>> The following code for your reference:
>>>
>>> def add(a:Int,b:Int):Int = {
>>> a + b
>>> }
>>>
>>> val d1 = sc.parallelize(1 to 10).map { i => (i, i+1, i+2) }
>>> val d2 = d1.map { i => (i._1, i._2, add(i._1, i._2))}
>>> d2.foreach(println)
>>>
>>>
>>> Otherwise, if your self-defining function is straightforward and you can
>>> represent it by SQL, using Spark SQL or DSL is also a good choice.
>>>
>>> case class Person(id: Int, score: Int, value: Int)
>>>
>>> val sqlContext = new org.apache.spark.sql.SQLContext(sc)
>>>
>>> import sqlContext._
>>>
>>> val d1 = sc.parallelize(1 to 10).map { i => Person(i,i+1,i+2)}
>>> val d2 = d1.select('id, 'score, 'id + 'score)
>>> d2.foreach(println)
>>>
>>>
>>> 2014-12-12 14:11 GMT+08:00 Nathan Kronenfeld <nkronenf...@oculusinfo.com
>>> >:
>>>
>>>> Hi, there.
>>>>
>>>> I'm trying to understand how to augment data in a SchemaRDD.
>>>>
>>>> I can see how to do it if can express the added values in SQL - just
>>>> run "SELECT *,valueCalculation AS newColumnName FROM table"
>>>>
>>>> I've been searching all over for how to do this if my added value is a
>>>> scala function, with no luck.
>>>>
>>>> Let's say I have a SchemaRDD with columns A, B, and C, and I want to
>>>> add a new column, D, calculated using Utility.process(b, c), and I want (of
>>>> course) to pass in the value B and C from each row, ending up with a new
>>>> SchemaRDD with columns A, B, C, and D.
>>>>
>>>> Is this possible? If so, how?
>>>>
>>>> Thanks,
>>>> -Nathan
>>>>
>>>> --
>>>> Nathan Kronenfeld
>>>> Senior Visualization Developer
>>>> Oculus Info Inc
>>>> 2 Berkeley Street, Suite 600,
>>>> Toronto, Ontario M5A 4J5
>>>> Phone: +1-416-203-3003 x 238
>>>> Email: nkronenf...@oculusinfo.com
>>>>
>>>
>>>
>>
>>
>> --
>> Nathan Kronenfeld
>> Senior Visualization Developer
>> Oculus Info Inc
>> 2 Berkeley Street, Suite 600,
>> Toronto, Ontario M5A 4J5
>> Phone: +1-416-203-3003 x 238
>> Email: nkronenf...@oculusinfo.com
>>
>
--
Nathan Kronenfeld
Senior Visualization Developer
Oculus Info Inc
2 Berkeley Street, Suite 600,
Toronto, Ontario M5A 4J5
Phone: +1-416-203-3003 x 238
Email: nkronenf...@oculusinfo.com
