I am attempting to load data from Azure Synapse DW into a dataframe as shown in the image.
However, I'm getting the following error:
AttributeError: 'DataFrameReader' object has no attribute 'sqlanalytics'
Traceback (most recent call last):
AttributeError: 'DataFrameReader' object has no attribute 'sqlanalytics'
Any thoughts on what I'm doing wrong?
That particular method has changed its name to synapsesql (as per the notes here) and is Scala only currently as I understand it. The correct syntax would therefore be:
%%spark
val df = spark.read.synapsesql("yourDb.yourSchema.yourTable")
It is possible to share the Scala dataframe with Python via the createOrReplaceTempView method, but I'm not sure how efficient that is. Mixing and matching is described here. So for your example you could mix and match Scala and Python like this:
Cell 1
%%spark
// Get table from dedicated SQL pool and assign it to a dataframe with Scala
val df = spark.read.synapsesql("yourDb.yourSchema.yourTable")
// Save the dataframe as a temp view so it's accessible from PySpark
df.createOrReplaceTempView("someTable")
Cell 2
%%pyspark
## Scala dataframe is now accessible from PySpark
df = spark.sql("select * from someTable")
## !!TODO do some work in PySpark
## ...
The above linked example shows how to write the dataframe back to the dedicated SQL pool too if required.
This is a good article for importing / export data with Synpase notebooks and the limitation is described in the Constraints section:
