Thanks Mike for this.
This is Scala. As expected it adds the id column to the end of the column
list starting from 0 0
scala> val df = ll_18740868.withColumn("id",
monotonically_increasing_id()).show
(2)
+---------------+---------------+---------+-------------+---
-------------------+-----------+------------+-------+---+
|transactiondate|transactiontype| sortcode|accountnumber|
transactiondescription|debitamount|creditamount|balance| id|
+---------------+---------------+---------+-------------+---
-------------------+-----------+------------+-------+---+
| 2009-12-31| CPT|'30-64-72| 18740868| LTSB STH
KENSINGT...| 90.0| null| 400.0| 0|
| 2009-12-31| CPT|'30-64-72| 18740868| LTSB CHELSEA
(309...| 10.0| null| 490.0| 1|
+---------------+---------------+---------+-------------+---
-------------------+-----------+------------+-------+---+
Can one provide the starting value say 1?
Cheers
Dr Mich Talebzadeh
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On 5 August 2016 at 16:45, Mike Metzger <m...@flexiblecreations.com> wrote:
> You can use the monotonically_increasing_id method to generate guaranteed
> unique (but not necessarily consecutive) IDs. Calling something like:
>
> df.withColumn("id", monotonically_increasing_id())
>
> You don't mention which language you're using but you'll need to pull in
> the sql.functions library.
>
> Mike
>
> On Aug 5, 2016, at 9:11 AM, Tony Lane <tonylane....@gmail.com> wrote:
>
> Ayan - basically i have a dataset with structure, where bid are unique
> string values
>
> bid: String
> val : integer
>
> I need unique int values for these string bid''s to do some processing in
> the dataset
>
> like
>
> id:int (unique integer id for each bid)
> bid:String
> val:integer
>
>
>
> -Tony
>
> On Fri, Aug 5, 2016 at 6:35 PM, ayan guha <guha.a...@gmail.com> wrote:
>
>> Hi
>>
>> Can you explain a little further?
>>
>> best
>> Ayan
>>
>> On Fri, Aug 5, 2016 at 10:14 PM, Tony Lane <tonylane....@gmail.com>
>> wrote:
>>
>>> I have a row with structure like
>>>
>>> identifier: String
>>> value: int
>>>
>>> All identifier are unique and I want to generate a unique long id for
>>> the data and get a row object back for further processing.
>>>
>>> I understand using the zipWithUniqueId function on RDD, but that would
>>> mean first converting to RDD and then joining back the RDD and dataset
>>>
>>> What is the best way to do this ?
>>>
>>> -Tony
>>>
>>>
>>
>>
>> --
>> Best Regards,
>> Ayan Guha
>>
>
>
