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From Michael Armbrust <mich...@databricks.com>
Subject Re: Spark SQL: Native Support for LATERAL VIEW EXPLODE
Date Sun, 27 Sep 2015 21:15:41 GMT
No, you would just have to do another select to pull out the fields you are
interested in.

On Sat, Sep 26, 2015 at 11:11 AM, Jerry Lam <chilinglam@gmail.com> wrote:

> Hi Michael,
>
> Thanks for the tip. With dataframe, is it possible to explode some
> selected fields in each purchase_items?
> Since purchase_items is an array of item and each item has a number of
> fields (for example product_id and price), is it possible to just explode
> these two fields directly using dataframe?
>
> Best Regards,
>
>
> Jerry
>
> On Fri, Sep 25, 2015 at 7:53 PM, Michael Armbrust <michael@databricks.com>
> wrote:
>
>> The SQL parser without HiveContext is really simple, which is why I
>> generally recommend users use HiveContext.  However, you can do it with
>> dataframes:
>>
>> import org.apache.spark.sql.functions._
>> table("purchases").select(explode(df("purchase_items")).as("item"))
>>
>>
>>
>> On Fri, Sep 25, 2015 at 4:21 PM, Jerry Lam <chilinglam@gmail.com> wrote:
>>
>>> Hi sparkers,
>>>
>>> Anyone knows how to do LATERAL VIEW EXPLODE without HiveContext?
>>> I don't want to start up a metastore and derby just because I need
>>> LATERAL VIEW EXPLODE.
>>>
>>> I have been trying but I always get the exception like this:
>>>
>>> Name: java.lang.RuntimeException
>>> Message: [1.68] failure: ``union'' expected but identifier view found
>>>
>>> with the query look like:
>>>
>>> "select items from purhcases lateral view explode(purchase_items) tbl as
>>> items"
>>>
>>> Best Regards,
>>>
>>> Jerry
>>>
>>>
>>
>

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