the use case is to fit a moving average model for stock prices with the
form:
x_n = \sum_{i = 1}^k \alpha_i * x_{n - i}

Can you please provide me the pseudo-code?


On Tue, Nov 19, 2013 at 4:30 PM, andy petrella <[email protected]>wrote:

> 1/ you mean like reshape in R?
> 2/ Or you mean by windowing the stream on a period basis?
>
> 1/ if you have RDD[Seq[Any]], you can have an RDD[Seq[Seq[Any]]] using
> `transform` then `sliding(6,6)` on the passed Seq
> 2/ > If the period is time you may check the method ending with `window`
> in DStream
>     > otherwise... I don't see the use case, so I'd have some difficulties
> helping you ^ ^
>
> Also, if you're building (row, col) pairs along with each cell data when
> the data is coming along, the PairedDStreamFunctions could help you if your
> put this pair as a key. But I'm just guessing...
>
> HTH (a bit :D)
>
> andy
>
>
> On Wed, Nov 20, 2013 at 1:01 AM, Michael Kun Yang <[email protected]>wrote:
>
>> Hi spark-enthusiasts,
>>
>> I am new to spark streaming. I need to convert streaming data into table.
>>
>> How to convert a data stream
>> {x_1, x_2, x_3, ..., x_n, ...}
>> into a table with the format:
>> x_1, x_2, x_3, x_4, x_5, x_6
>> x_2, x_3, x_4, x_5, x_6, x_7
>> ...
>> x_{n + 1}, x_{n + 2}, ..., x_{n + 7}
>> ...
>>
>> Thank you very much!
>>  -Kun
>>
>
>

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