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Good morning
Greetings to all.
Microsoft Fabric was recently added to the organization and I have been exploring the service in order to get the most out of it.
I want to use datamart and lakehouse service, but for now I have the following question:
How can I write the table in the tables section.
I add the simple code that I am using, if you wish you can replicate it, it is an open government data page.
As you can see, I am using the R language to read the API, but for now I cannot save this table. If anyone can help me, thanks in advance.
Additionally, if you know of resources where I can learn to use these new resources (datamart, lakehouse, pipeline...), I would greatly appreciate it.
Solved! Go to Solution.
Hi @jcamilo1985 - Thanks for using Fabric Community,
As I understand you are very new to fabric and sparkR, would like to learn explore things on it.
I am sharing few links that helps you get more insights with fabric and sparkR.
Fabric Link: It helps you understand these new resources (datamart, lakehouse, pipeline...)
Get started with Microsoft Fabric - Training | Microsoft Learn
Spark R Link: helps to understand how to use SparkR
SparkR overview - Azure Databricks | Microsoft Learn
Tutorial: Work with SparkR SparkDataFrames on Databricks | Databricks on AWS
I was able to create a table in lakehouse using below code, attached screenshot for reference -
# tableName <- "<catalog-name>.<schema-name>.<table-name>"
tableName <- "gopi_lake_house.abc"
data <- list(
list(1L, "Raymond", "green", "apple"),
list(2L, "Loretta", "purple", "grape"),
list(3L, "Wayne", "yellow", "banana")
)
schema <- structType(
structField("id", "integer"),
structField("name", "string"),
structField("color", "string"),
structField("fruit", "string")
)
df <- createDataFrame(
data = data,
schema = schema
)
saveAsTable(
df = df,
tableName = tableName
)
# Verify that the table was successfully saved by
# displaying the table's contents.
display(sql(paste0("SELECT * FROM ", tableName)))
Hope this helps your query. Happy Learning.!
If you want to use an easier no code solution for a simple data ingestion, you will find pipelines a much better choice. You can start creating a pipeline, and click on copy data, and it should be pretty straight forward to figure out the rest of the steps. If you still get stuck refer this tutorial https://learn.microsoft.com/en-us/fabric/data-factory/tutorial-end-to-end-pipeline
Hi @jcamilo1985 - Thanks for using Fabric Community,
As I understand you are very new to fabric and sparkR, would like to learn explore things on it.
I am sharing few links that helps you get more insights with fabric and sparkR.
Fabric Link: It helps you understand these new resources (datamart, lakehouse, pipeline...)
Get started with Microsoft Fabric - Training | Microsoft Learn
Spark R Link: helps to understand how to use SparkR
SparkR overview - Azure Databricks | Microsoft Learn
Tutorial: Work with SparkR SparkDataFrames on Databricks | Databricks on AWS
I was able to create a table in lakehouse using below code, attached screenshot for reference -
# tableName <- "<catalog-name>.<schema-name>.<table-name>"
tableName <- "gopi_lake_house.abc"
data <- list(
list(1L, "Raymond", "green", "apple"),
list(2L, "Loretta", "purple", "grape"),
list(3L, "Wayne", "yellow", "banana")
)
schema <- structType(
structField("id", "integer"),
structField("name", "string"),
structField("color", "string"),
structField("fruit", "string")
)
df <- createDataFrame(
data = data,
schema = schema
)
saveAsTable(
df = df,
tableName = tableName
)
# Verify that the table was successfully saved by
# displaying the table's contents.
display(sql(paste0("SELECT * FROM ", tableName)))
Hope this helps your query. Happy Learning.!
Thank you very much for responding to the request, this solution indeed works.
Thanks for the links, now let's learn.
Hello @jcamilo1985 ,
We haven’t heard from you on the last response and was just checking back to see if your query got resolved? Otherwise, will respond back with the more details and we will try to help.
Thank you
Hi @jcamilo1985 ,
We haven’t heard from you on the last response and was just checking back to see if your query got resolved? Otherwise, will respond back with the more details and we will try to help.
Thank you
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