Dynamic columns are handled in CQL using either map collections or
clustering columns or a combination of the two.

-- Jack Krupansky

On Tue, Feb 2, 2016 at 10:11 PM, Anuj Wadehra <anujw_2...@yahoo.co.in>
wrote:

> By dynamic columns, I mean columns not defined in schema. In current
> scenario, every row has some data in columns which are defined in schema
> while rest of the data is in columns which are not defined in schema. We
> used Thrift for inserting data.
>
> In new schema, we want to create a collection column and put all the data
> which was there in columns NOT defined in schema to the collection.
>
>
> Thanks
> Anuj
>
> Sent from Yahoo Mail on Android
> <https://overview.mail.yahoo.com/mobile/?.src=Android>
>
> On Wed, 3 Feb, 2016 at 12:36 am, DuyHai Doan
> <doanduy...@gmail.com> wrote:
> You 'll need to do the transformation in Spark, although I don't
> understand what you mean by "dynamic columns". Given the CREATE TABLE
> script you gave earlier, there is nothing such as dynamic columns
>
> On Tue, Feb 2, 2016 at 8:01 PM, Anuj Wadehra <anujw_2...@yahoo.co.in>
> wrote:
>
>> Will it be possible to read dynamic columns data from compact storage and
>> trasform them as collection e.g. map in new table?
>>
>>
>> Thanks
>> Anuj
>>
>> Sent from Yahoo Mail on Android
>> <https://overview.mail.yahoo.com/mobile/?.src=Android>
>>
>> On Wed, 3 Feb, 2016 at 12:28 am, DuyHai Doan
>> <doanduy...@gmail.com> wrote:
>> So there is no "static" (in the sense of CQL static) column in your
>> legacy table.
>>
>> Just define a Scala case class to match this table and use Spark to dump
>> the content to a new non compact CQL table
>>
>> On Tue, Feb 2, 2016 at 7:55 PM, Anuj Wadehra <anujw_2...@yahoo.co.in>
>> wrote:
>>
>>> Our old table looks like this from cqlsh:
>>>
>>> CREATE TABLE table table1 (
>>>   key text,
>>>   "Col1" blob,
>>>   "Col2" text,
>>>   "Col3" text,
>>>   "Col4" text,
>>>   PRIMARY KEY (key)
>>> ) WITH COMPACT STORAGE AND …
>>>
>>> And it will have some dynamic text data which we are planning to add in
>>> collections..
>>>
>>> Please let me know if you need more details..
>>>
>>>
>>> Thanks
>>> Anuj
>>> Sent from Yahoo Mail on Android
>>> <https://overview.mail.yahoo.com/mobile/?.src=Android>
>>>
>>> On Wed, 3 Feb, 2016 at 12:14 am, DuyHai Doan
>>> <doanduy...@gmail.com> wrote:
>>> Can you give the CREATE TABLE script for you old compact storage table ?
>>> Or at least the cassandra-client creation script
>>>
>>> On Tue, Feb 2, 2016 at 3:48 PM, Anuj Wadehra <anujw_2...@yahoo.co.in>
>>> wrote:
>>>
>>>> Thanks DuyHai !! We were also thinking to do it the "Spark" way but I
>>>> was not sure that its would be so simple :)
>>>>
>>>> We have a compact storage cf with each row having some data in staticly
>>>> defined columns while other data in dynamic columns. Is the approach
>>>> mentioned in link adaptable to the scenario where we want to migrate the
>>>> existing data to a Non-Compact CF with static columns and collections ?
>>>>
>>>> Thanks
>>>> Anuj
>>>>
>>>> --------------------------------------------
>>>> On Tue, 2/2/16, DuyHai Doan <doanduy...@gmail.com> wrote:
>>>>
>>>>  Subject: Re: Moving Away from Compact Storage
>>>>  To: user@cassandra.apache.org
>>>>  Date: Tuesday, 2 February, 2016, 12:57 AM
>>>>
>>>>  Use Apache
>>>>  Spark to parallelize the data migration. Look at this piece
>>>>  of code
>>>> https://github.com/doanduyhai/Cassandra-Spark-Demo/blob/master/src/main/scala/usecases/MigrateAlbumsData.scala#L58-L60
>>>>  If your source and target tables
>>>>  have the SAME structure (except for the COMPACT STORAGE
>>>>  clause), migration with Spark is a 2 lines of
>>>>  code
>>>>  On Mon, Feb 1, 2016 at 8:14
>>>>  PM, Anuj Wadehra <anujw_2...@yahoo.co.in>
>>>>  wrote:
>>>>  Hi
>>>>  Whats the fastest and reliable way
>>>>  to migrate data from a Compact Storage table to Non-Compact
>>>>  storage table?
>>>>  I was not
>>>>  able to find any command for dropping the compact storage
>>>>  directive..so I think migrating data is the only way...any
>>>>  suggestions?
>>>>  ThanksAnuj
>>>>
>>>>
>>>>
>>>
>>
>

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