Im trying to create a Delta live table with the source data from azure synapse table. I used spark.read() method and ran in DLT pipeline, But the pipeline creates a Materialised view instead of DLT table.

And then, i tried using spark.readStream(), but that couldn’t support synapse analytics as a format.

Suggest me some methods to create a DLT table with the source data is from a table present in Azure Synapse

I tried the below code which is creating a materialised view instead of a DLT table. Here the TableQuery have a select statement which gets records from the synapse table.

@dlt.table(
  name=TargetTableName,
  comment="Landing to Bronze layer",
  table_properties={"quality": "bronze"}
  )
def table_load():
  df = (
    spark.read
    .format("com.databricks.spark.sqldw")
    .option("url", ConnectionURL)
    .option("tempDir", TempLocation)
    .option("enableServicePrincipalAuth", "true")
    .option("query", TableQuery)
    .load()
  )
  return df