Doesn't directly answer your question but there are ways in scala and
pyspark - See if this helps:
https://repost.aws/questions/QUP_OJomilTO6oIgvK00VHEA/writing-data-to-kinesis-stream-from-py-spark
On Thu, Feb 16, 2023, 8:27 PM hueiyuan su wrote:
> *Component*: Spark Structured Streaming
> *Leve
*Component*: Spark Structured Streaming
*Level*: Advanced
*Scenario*: How-to
*Problems Description*
I would like to implement witeStream data to AWS Kinesis with Spark
structured Streaming, but I do not find related connector jar can be used.
I want to check whether fully
I think these 4 steps should help:
Use zip
Explode
Withcolumn (getelement of array)
Drop the array column
Thanks
On Thu, Feb 16, 2023, 2:18 PM sam smith wrote:
> @Enrico Minack I used arrays_zip to merge values
> into one row, and then used toJSON() to export the data.
> @Bjørn explode_oute
@Enrico Minack I used arrays_zip to merge values
into one row, and then used toJSON() to export the data.
@Bjørn explode_outer didn't yield the expected results.
Thanks anyway.
Le jeu. 16 févr. 2023 à 09:06, Enrico Minack a
écrit :
> You have to take each row and zip the lists, each element of
Use explode_outer() when rows have null values.
tor. 16. feb. 2023 kl. 16:48 skrev Navneet :
> I am not expert, may be try if this works:
> In order to achieve the desired output using the explode() method in
> Java, you can create a User-Defined Function (UDF) that zips the lists
> in each row a
Hi all,
I am sorry to bother you, I have a problem and I hope to get your help. I want
to use spark to customize the data source based on ParquetDataSourceV2 class in
spark v3.2.2, but I want to leave out the location field and then modify the
table and partition path in the code. How can I do
I am not expert, may be try if this works:
In order to achieve the desired output using the explode() method in
Java, you can create a User-Defined Function (UDF) that zips the lists
in each row and returns the resulting list. Here's an example
implementation:
typescript
Copy code
import org.apach
You can try this
gsutil cp src/StructuredStream-on-gke.py gs://codes/
where you create a bucket on gcs called codes
Then in you spark-submit do
spark-submit --verbose \
--master k8s://https://$KUBERNETES_MASTER_IP:443 \
--deploy-mode cluster \
--name
You have to take each row and zip the lists, each element of the result
becomes one new row.
So turn write a method that turns
Row(List("A","B","null"), List("C","D","null"), List("E","null","null"))
into
List(List("A","C","E"), List("B","D","null"), List("null","null","null"))
and use flatm
