For elasticsearch you can use the elastic official connector.
https://www.elastic.co/what-is/elasticsearch-hadoop
Elastic spark connector docs:
https://www.elastic.co/guide/en/elasticsearch/hadoop/current/spark.html
On Thu, May 14, 2020, 21:14 Amol Umbarkar wrote:
> Check out sparkNLP for tokenization. I am not sure about solar or elastic
> search though
>
> On Thu, May 14, 2020 at 9:02 PM Rishi Shah
> wrote:
>
>> This is great, thanks you Zhang & Amol !!
>>
>> Yes we can have multiple tags per row and multiple regex applied to
>> single row as well. Would you have any example of working with spark &
>> search engines like Solar, ElasticSearch? Does Spark ML provide
>> tokenization support as expected (I am yet to try SparkML, still a
>> beginner)?
>>
>> Any other reference material you found useful while working on similar
>> problem? appreciate all the help!
>>
>> Thanks,
>> -Rishi
>>
>>
>> On Thu, May 14, 2020 at 6:11 AM Amol Umbarkar
>> wrote:
>>
>>> Rishi,
>>> Just adding to zhang's questions.
>>>
>>> Are you expecting multiple tags per row?
>>> Do you check multiple regex for a single tag?
>>>
>>> Let's say you had only one tag then theoretically you should be do this -
>>>
>>> 1 Remove stop words or any irrelevant stuff
>>> 2 split text into equal sized chunk column (eg - if max length is
>>> 1000chars, split into 20 columns of 50 chars)
>>> 3 distribute work for each column that would result in binary
>>> (true/false) for a single tag
>>> 4 merge the 20 resulting columns
>>> 5 repeat for other tags or do them in parallel 3 and 4 for them
>>>
>>> Note on 3: If you expect single tag per row, then you can repeat 3
>>> column by column and skip rows that have got tags in prior step.
>>>
>>> Secondly, if you expect similarity in text (of some kind) then you could
>>> jus work on unique text values (might require shuffle, hence expensive) and
>>> then join the end result back to the original data. You could use hash of
>>> some kind to join back. Though I would go for this approach only if the
>>> chances of similarity in text are very high (it could be in your case for
>>> being transactional data).
>>>
>>> Not the full answer to your question but hope this helps you brainstorm
>>> more.
>>>
>>> Thanks,
>>> Amol
>>>
>>>
>>>
>>>
>>>
>>> On Wed, May 13, 2020 at 10:17 AM Rishi Shah
>>> wrote:
>>>
Thanks ZHANG! Please find details below:
# of rows: ~25B, row size would be somewhere around ~3-5MB (it's a
parquet formatted data so, need to worry about only the columns to be
tagged)
avg length of the text to be parsed : ~300
Unfortunately don't have sample data or regex which I can share freely.
However about data being parsed - assume these are purchases made online
and we are trying to parse the transaction details. Like purchases made on
amazon can be tagged to amazon as well as other vendors etc.
Appreciate your response!
On Tue, May 12, 2020 at 6:23 AM ZHANG Wei wrote:
> May I get some requirement details?
>
> Such as:
> 1. The row count and one row data size
> 2. The avg length of text to be parsed by RegEx
> 3. The sample format of text to be parsed
> 4. The sample of current RegEx
>
> --
> Cheers,
> -z
>
> On Mon, 11 May 2020 18:40:49 -0400
> Rishi Shah wrote:
>
> > Hi All,
> >
> > I have a tagging problem at hand where we currently use regular
> expressions
> > to tag records. Is there a recommended way to distribute & tag? Data
> is
> > about 10TB large.
> >
> > --
> > Regards,
> >
> > Rishi Shah
>
--
Regards,
Rishi Shah
>>>
>>
>> --
>> Regards,
>>
>> Rishi Shah
>>
>
